Master of Science in Business Analytics

Botao (Arthur) An

Botao An graduated with high honors from Central University of Finance and Economics with a dual degree in marketing and finance, a combination that provided him with a solid quantitative foundation for business analytics. Throughout coursework, Botao was fascinated by the great power of data and became a data enthusiast who is determined to pursue a career in this field.

During Botao’s internship at E&Y Advisory Department, he analyzed more than 5 Terabytes of auto user data with linear regression, logistic regression and Principal Components Analysis (PCA) and derived informative insights about auto user behaviors. While interning at Nielsen, he collected data with SQL query, visualized the data with Tableau and presented client with user-friendly executive summaries. Botao also used python to develop a convenient toolkit to do text analytics, increasing working efficiency by 200%. At Hillhouse Capital Group, the biggest private equity company in Asia, he identified the risks and bottlenecks of Hillhouse Capital Trading Department, implemented process mining and developed a workflow management system with VBA programming, helping trading team achieve recognized best practice. Additionally, he conducted CRM analysis for the purchase of Belle International, China’s largest footwear retailer. Botao’s past coursework and internships have helped him develop an analytical mindset and enabled him to solve problems with disciplined approaches.

Botao is excited to dive deeper into data analytic at the MS in Business Analytics program at UCLA Anderson, leveraging the exhaustive curriculum to get more understandings of machine learning, neural network, predictive models and data management. Through these practical analytical skills and hand-on group projects, Botao is looking forward to unleashing the power of data analytics, generating unique insights, making informed decisions and creating better customer experience in the real business world.

Bopaiah Subbaiah

Subbaiah graduated Summa Cum Laude with a B.S. in Mechanical Engineering and B.A. in Economics from the University of California, Los Angeles. As an undergraduate, he was a member of Tau Beta Pi and took part in various student leadership and mentor roles on campus. He gravitated towards the field of analytics when he learned the possible application of analytics to business decisions on his family’s coffee farm in rural India. He is particularly passionate about combining technology’s potent quantitative methods and business’s rigorous qualitative analysis to make intelligent, socially impactful, and practical decisions.

After graduation, Subbaiah interned at Anheuser Busch InBev. During his internship, he developed a price elasticity model for the United States at the zip code level. He processed, filtered and presented millions of rows of data and developed the model using the BLP algorithm in R to estimate the effect of price increase of own and competitor brands on volume share. The model could estimate elasticities for thousands of SKUs and could incorporate preference heterogeneity and changing demographics over time. Additionally, the model could estimate whether an increase in price of an own brand would collectively increase/decrease total market share of all own brands in different segments. As a result, similar models were developed for brands in other countries.

Today, Subbaiah views analytics and machine learning as the way into solving the world’s biggest problems. He wishes to utilize his data science experience in Anheuser Busch InBev, along with his current Masters in Business Analytics from UCLA Anderson and undergraduate degrees in Mechanical Engineering and Economics, with the perspective gained through his childhood in a coffee farm to:

• Developing sustainable technologies to decrease human impact on the environment.
• Increasing process efficiency in every realm from daily activities to complex business problems.
• Making advanced technology more accessible to all.

Subbaiah intends to leverage the exhaustive curriculum of the MSBA program at UCLA Anderson to get a comprehensive understanding of predictive analytics, machine learning, deep learning and natural language processing. It is the opportunity he dreamed of and he looks forward to the hands-on experience of teasing out data insights that previously lay hidden. The engineer in him is thrilled to impact a company’s efficiency and decision-making and hopes to become an accomplished data scientist who can do just that.

Sebastian Budnik

Sebastian was born and raised in Santiago, Chile. He graduated as an Industrial Engineer from the University of Chile, where he got a solid formation in science, technology, engineering processes and analytical skills. Along the career he cultivated a special interest in areas of operation management and business strategy, with focus in modeling complex system, collecting the data and interpreting results and trends. For his thesis project and first job, he designed and built a balanced scorecard to successfully implement a new strategy plan at the manufactured paper division of CMPC, one of the largest cellulose and paper companies in the world.

For the past years Sebastian worked at TotalPack, the Chilean leading company in customer service solutions, queue management systems and self-service machines. There, he actively participated in many innovative technology projects for organizations from many sectors like telecommunications, banking, retail, health and public services. All these projects related to strategic data management of their client’s attention processes, used after to improve their operational efficiency and customer service.

One of his last projects was about upgrading queue management in assisted sales spaces like supermarket and pharmacy national chains. He implemented a digital solution to allow automatic and continuous data collection. The analysis of this data enabled a better allocation of human resources, improving operational efficiency. In addition, this new approach led to an enhanced customer buying experience.

He has seen from his experience that thousands of rich data records collected every day are stored but left underused, missing the opportunity to enrich clients’ experiences and to improve companies’ efficiencies. Therefore, he strongly believes that studying at UCLA and being part of the Master in Business Analytics will enable him to gain the knowledge and skills needed to develop better customer solutions through data management, while being immersed in the new wave of technology.

Pedro (Moises) Camacho

Moises started solving business problems in a young age while working for the family business. This early exposure of running a small business gave him a sense of the essentials gears involved on this complicated machinery; how identifying the right business problems and solving them is the most important part of successful organization and yet it is always overlooked.

After graduation from high school Moises enrolled in a bachelor’s degree in economics to further understand how the whole economy works. He was particularly interested subjects related on how people make decisions: micro-economics, marketing, behavioral economics, among others. This is the most important question that a business can answer and knowing the human’s predispositions is paramount.

Right after graduation Moises did an internship for a market consultancy company; where he led quantitative studies, redacted surveys, gave presentations and use data to drag conclusions. After finishing the internship, he landed a job in brand new unit at the Internal Revenue Office of Dominican Republic, where he generated audit strategies tailor made for specific sectors.

After 5 months Moises was selected to lead the newly created unit of 5 analysts. His priority at this stage was to standardize the processes so that the workload was scalable. He also focused on creating a companies’ risk score, to select companies to audit. At the end of his tenure of almost 3 years he had led more than 25 research paper, generated the score system and generated strategies for automatics audits.

While leading the team at the Internal Revenue office Moises won the startup weekend and started an online market platform in the Dominican Republic. Also, he developed an automatic model to valuate companies in the stock market, which evolved to what it’s now Towers Capital Group where he is a founder and technical advisor.

Moises has a master’s degree in economics from Huazhong University of Science and Technology (where he learned Chinese) and a specialization in data science. He is currently enrolled in a MS in Business Analytics at Anderson.

Hua (Lucy) Chai

Lucy graduated from the University of California, Los Angeles in 2016 with a B.A. in Business Economics and a minor in Accounting. She is passionate about using modeling and business financial analysis to help clients make executable, intelligent, and impactful decisions. In addition to coursework, she spent six month providing market entry strategies adopted by a non-for-profit company, and was later funded by angel investors.

After graduation, Lucy joined Ernst & Young, where she interacted with technology industry clients in execution, interviewing and documentation of R&D studies. Lucy also strengthened her knowledge in finance and business operation by working on various financial statements, cash reconciliations and corporations tax returns across industries. Lucy is eager to sharp her abilities in transferring data concepts into business value and address client’s needs. When Lucy was working as an analytics intern at Mu Sigma Shanghai office before join Anderson, she helped retail clients to analyze and improve consumer segmentation to deliver business insights.

The idea of connecting various information intelligently, and the ability to translate complex problems into viable solutions has motivated Lucy to pursue the master’s degree in Business Analytics at UCLA Anderson, and dive deep into consumer analysis. Lucy is looking forward to leveraging her analytical skills and business background to tackle problems logically and creatively, and pivot marketing data into strategic decisions, with a cohort of talented aspiring analysts.

Walid Fenianos

Walid is a performance-driven Project Management Professional (PMP) with more than nine years of project management and technical expertise. He is skilled at cultivating client relationships and driving revenue growth in high-pressure environments. He has experience in working with R, Python, Tableau, and advanced Excel. He is passionate about advanced machine learning and deep learning and is continuously working on developing his skills and knowledge in those areas through his graduate coursework at UCLA, online courses, and professional workshops.

Walid received a bachelor’s in engineering in 2008 from the school of engineering at the Lebanese American University (LAU). In 2013, he graduated from Notre Dame University with a Bachelor of Business Administration with highest distinction. He earned his PMP in 2014 and went on to pass the Chartered Financial Analyst (CFA) level II exam in 2015.

Upon graduating, he held a job as a Business Improvement Specialist at INKRIPT Holding, a security printing company, where he worked for two years. In 2010, he moved to Affrad Holding (later rebranded to Global Assure Finance), a consolidation of several legal entities active in the insurance, brokerage, and technology fields throughout the MENA (Middle East and North Africa) region, where he was hired as a Project Coordinator, while concurrently pursuing his Bachelor of Business Administration degree.

In 2015, Walid founded EON For Training And Development in Beirut, offering CFA – PMP – GMAT – CMA – SHRM (CP & SCP) training. Through EON, he was able to vigorously promote his courses – especially the CFA Level I course –at a very low marketing cost, thereby acquiring the second largest market share (where CFA courses were concerned).

Less than two years into EON, a prominent investor grew interested in the company and submitted an offer to acquire it. Walid then sold EON, with the exception of the GMAT and PMP courses, which he continued to develop through KeyLearn, his next venture. He developed the curricula, learning platform and its content, marketing material, agreement with instructors etc., and signed on several clients before once again selling his second company to join the Master’s in Business Analytics (MSBA) program at the Anderson Business School at UCLA.

Diqing (Fei) Fei

Fei graduated with first class honors from the City University of Hong Kong with a major in Information Engineering, which sharped her abilities to tackle problems with a logical and innovative approach. Throughout her coursework, Fei was intrigued by permutations that could impact image processing and conducted research on network optimization. In addition to her coursework, Fei spent one summer producing Business Intelligence report using data mining & BusinessObject software for an upscale department store in Hong Kong.

After graduation, Fei joined SWIFT – an international community of financial institution founded in 1973 that helps create financial telecommunication solutions. As a system analyst, Fei supported the core financial messaging platform which handles 30 million financial messages like securities, payments and treasuries every day, and further applied her analytical skills to solve technical challenges. Fei has extensive experience in writing SQL/perl/shell scripts to extract, clean and analyze data, and leveraged her skills to develop webpage and created reports to present data trends. In addition to her technical skills, Fei worked as part of a team where she collaborated globally with multiple departments to ensure the accuracy of her deliverables. Fei played a leading role in many projects and added unique values to the team by combining innovation with her technical background.

Years of experience in tackling financial messaging data made Fei realize her passion in data science. Pursuing her Master of Science in Business Analytics at UCLA Anderson, Fei is excited to dive deep into the data mining algorithms and machine learning implementations. With a cohort of talented aspiring scientists, Fei looks forward to transforming data into comprehensive visual formats, and achieve insightful business decisions.

Pi-Chin Feng

Pi-Chin graduated from National Taiwan University in 2014 with a B.A in Economics. Throughout her academic studies, Pi-Chin has focused on economics, statistics, marketing analytics and customer behavior analytics. She developed an interest in analytics first through her coursework, and later through an internship experience and full-time working experience in the internet industry.

After graduation, she started her career at a Low-Cost Airline company as an e-commerce specialist. Compared with Legacy Carriers, online channel, including airlines’ proprietary websites, online travel agents (OTAs), and metasearch websites become the major channel for search and booking tickets. By gathering customer data and analyzing this information, she was able to identify trends and conclude different ticket buying behavior based on the destination and to generate user segment. According to the analyzed result, she had utilized the marketing strategy and efficiently increase the company’s total revenue. Besides this, Pi-Chin was an experienced product manager in a tech start-up company, focusing on developing online user behavior analysis platform. As a product manager, she worked closely with data scientists and data engineers in her team, and therefore developed a keen interest in data science.

At UCLA Master of Science in Business Analytics program, Pi-Chin is ready to build upon her academic and professional background in analytics. She is most interested in predictive analytics, customer analytics, and competitive analytics. She looks forward to gaining more skills need to help business to solve impactful data problems and to build more comprehensive understandings of their customer. Moreover, she is excited to collaborate with her cohorts on academic and industry projects, improve her knowledge of business analytics, and leverage her previous experiences into practical and innovative solutions.

Xiaosong (Steve) Gao

Steve obtained his undergrad degree from USC Marshall with a focus in Finance and Operations Management. After graduation, he joined Deloitte Analytics as a consultant and later co-founded a startup focusing on retail analytics and data management.

As a life explorer, Steve has traveled around the world at a very young age and speaks 4 languages. With a love of adventure, an intellectual curiosity and a dedication to excellence, Steve strives to deliver the best results to his colleagues and clients.

Outside of the professional world, Steve is a trained sommelier, an enthusiastic rock-climber, swimmer and martial artist. He also has interests in linguistics, classic studies and international relations.

Xinyi Guan

Xinyi received her bachelor degree in chemistry and economics from Peking University. Throughout her college years, she was intrigued by the charm of quantitative research and data-driven solutions. During her past internships, she has experienced in data visualization and modeling for real-business problems. For example, as an intern in a start-up real estate consulting company, she was involved in generating potential homebuyers moving pattern on city maps by using cellphone GPS information, which contributed to creating typical customer portraits. Also, during the internship in Kantar Millward Brown ACSR, a quantitative marketing research agency, she utilized factor analysis and MDS model (specifically designed for brand power calculation) to process raw data to quantify the brand influence of Chinese brands in the oversea markets.

Through the MSBA program, Xinyi is excited to expand knowledge about analytics and accumulate experience in programming and statistical modeling. She hopes to pursue a career in the combination of business solution and data science.

Nandini Hedge

Nandini gravitated towards the field of analytics while leading a market research project for one of India’s largest entertainment companies while pursuing her MBA from one of the reputed schools in India. She also ended up winning the first prize for submitting this report wherein she analyzed user data to connect covert desires to television content preferred by different demographics. During this time, she also had the opportunity to intern at Google India with the SMB Sales team.

Nandini previously earned her Bachelor of Engineering in Information Technology from Mumbai University and worked briefly as a software engineer. This gave her the required programming experience to pursue professional certifications in languages such as SAS, R and Python.

Post MBA she went on to work as a Business Analyst with the corporate operational excellence team at Cognizant. Here she was involved in several corporate strategic programs which majorly dealt with revenue monetization and margin optimization. She was mainly responsible for analyzing unstructured and structured data, identifying metrics and developing the right model which often ended up saving millions of dollars in revenue for the organization. Shortly after she moved to a Tech consulting role in the Silicon Valley wherein she worked with an AI client which developed virtual assistants/chatbots as a product. As an analyst her role majorly revolved around gathering business requirements and analyzing the user queries to generate insights that improved bot usage.

Through her varied experiences, she developed a keen interest in studying data science in-depth which is what bought her to study MS Business Analytics at UCLA Anderson. In here she aims to leverage her business experience and develop the required data analytics skills to make in-roads into the dynamic world of data science.

Guanhua (Victor) Huang

"To me, mathematics, computer science, and the arts are insanely related. They're all creative expressions." -Professor Sebastian Thrun

A computer has always been the most critical part of Guanhua's Life. When he was growing up in China, Guanhua wanted to become a scientist to unveil the world. Being a quick learner with strong curiosity, he was admitted by the University of Pittsburgh with a major in chemistry and a minor in mathematics. During college, he was attracted by the interdisciplinary field of Computational Chemistry, which introduced him to how theory is used to standardize multiple chemical phenomena and how computer modelling is used to address scientific problems.

Later, he moved to California to pursue a PhD degree in Computational Chemistry from the University of California at Los Angeles. He extensively designed and implemented optimization and sampling algorithms to solve chemistry problems, wisely and rigorously. The way of critical thinking has been part of him and has shaped his life attitudes. However, he was bored by proving the same theory in different chemical systems, though he could obtain a lot of high index publications. So, he chose to pursue a master's degree as a business analyst to quantitatively understand the world. During that period, he worked as a graduate research with Professor Misic Velibor to develop an R package called TreeEnsembleOptimization. He also worked as a research analyst at Los Angeles Capital group, focusing on implementing big-data oriented factor models in Python and developed Markov Decision Process (MDP) based trading algorithm. 

His knowledge horizon has been enormously broadened since he joined the MSBA program at UCLA. As a prospective data analyst, he understands how important it is to keep updated in various aspects of programming, statistics and business sense. Right now, he is studying deep learning and algorithms in the MSBA program, and various advanced statistics courses at UCLA. He is confident that the MSBA program at UCLA could definitely deepen his understanding of data science and help him become the successful data scientist he has always dreamed of being.

                                                                                                                                                                                                                                                                                                                                                                               

Travis Huang

Travis Huang is an advanced analytics specialist with a background in investments and energy. As the leader of a team of analysts at a private equity fund, he became proficient in econometric modeling, cross-sectional time-series analysis, and demand forecasting. His team focused the evaluation of downstream Oil & Gas export opportunities in the United States, which required analyzing the energy markets of South and East Asia as well as the competitive landscape of the Middle East and Russia. Prior to his career in finance, he was a business analyst at residential solar power company called Verengo Solar Plus. At Verengo, he developed an estimation tool in Excel, which accepted inputs from sales reps in the field to quickly generate energy production predictions of rooftop solar systems.

Travis graduated from the USC Marshall School Business with a B.S. in Business Administration in 2009, with dual degree concentrations in Finance and Entrepreneurship. He has always been interested experimenting with technology to yield productivity gains and cost savings in his work. After reading a Medium post in 2014 that described how machine learning and A.I. would reshape the landscape of the venture capital and private equity industry, he decided to pick up learning Python as a side hobby. He became enraptured by the freedom and flexibility afforded by open source frameworks, later learning to code in other languages such as R and Java.

He currently serves as president of the inaugural class of the M.S. in Business Analytics program at the UCLA Anderson School of Management, where he is constantly inspired by his classmates’ breadth of worldly perspectives, work ethic, and professional backgrounds. Most recently, he accepted a teaching position as a part-time Data Science instructor at General Assembly, where he is empowering working professionals to drive significant impact in their work by employing the data visualization, feature engineering, and algorithmic modeling skills taught by the program.

Travis is fascinated by the innumerable ways in which modern machine learning and neural networks have been applied in solving business problems for firms that have traditionally relied on more qualitative decision making. Through the continued refinement of his skillset from the rigorous analytics-centric curriculum and hands-on corporate sponsored Capstone projects provided by the MSBA program at Anderson, Travis hopes leverage the power of big data to enable organizations to develop more customer-centric products, make data-driven decisions more confidently, and foster innovation in their industries.

Junaid Ikram

After graduated in Electircal Engineering in 2006, I joined Schlumberger data evaluation segment, world's leading service provider in Oil & Gas, and worked on various international assignments. During this time, I got an opportunity to work for various roles ranging from engineering to operations analytics and strategy. Moreover, recently I got an opportunity to work for City of Los Angeles Mayor's office as a summer Data Science intern, where I was involved not only in building prototype of data schema for homeless initiatives project, but also in building machine learning models to predict the likelihood of employees' retirement so that city can plan both work force and pension funds in an optimized manner.

Historically, I have been involved in operations analytics and strategy projects at number of instances, however, I am very passionate about increasing Customer Life Time Value as well as customer acquisition using various analytical and statistical methods. Moreover, I love finding innovative ways of measuring churn by using various analytics skills, such as analytics on unstructured data, to bring value proposition to clients.  

Aniket Jain

Passion, Persistence, Positivity, and Playfulness are the characteristics that aptly define Aniket. He is passionate about working with data to derive analytical insights, persistent in his efforts to overcome obstacles and roadblocks, positive to accept and learn from failures and playful to maintain a smile on his face when translating the findings into business recommendations.

Aniket graduated with a degree in Master of Management from Indian Institute of Technology, Mumbai. After graduation, he worked with one of India's largest finance company as a Data Analyst for over four years. In this role, he was involved in various meticulous analytics projects aimed at providing strategic insights and actionable recommendations for the company. Previously having a bachelor's degree in engineering and experience of working as a business analyst and programmer for three years at Tata Consultancy Services gives him aptitude to understand algorithms well and design efficient machine learning models. Using this experience and in-depth business understanding he designed a predictive model to assess customers' time on books based on transaction size, type of product, the rate of interest, sector and other parameters of business significance. The model highlighted the customers likely to have a high attrition probability and hence, more attention could be given to such accounts to retain them. The model was appreciated by the top management, including the CEO of the organization, and widely used resulting in additional revenue of ~$1M. 

As a summer intern at The City of Los Angeles, Controller's office, he worked on predicting the likelihood of retirement of employees. Based on various demographic factors and job-specific attributes, the model would estimate the duration after which an employee would retire. The output of this model is a critical input in work-force planning exercise across the City of Los Angeles from point of view of maintaining efficiency and continuity.

Aniket has a good mix of strong technical skills and acute managerial acumen which enables him to tackle any business problem holistically. Furthermore, his dedication keeps him on the task and creativity enables him to find ways around roadblocks that may come in the pursuit. Following graduation from MS Business Analytics at UCLA Anderson, he intends to focus his energies towards roles where he will make data-intensive decisions that enhance business operations.

Namita Kallianpurkar

Namita Kallianpurkar comes into the MSBA Class of 2018 after working for 8 years in marketing analytics and data-focused consulting. As a Marketing Manager at Arista Networks, Namita led a lean marketing analytics team that used customer and event data to steer corporate marketing strategy as the company went through a successful IPO, eventually reaching an annual revenue of $1B. Through a blend of strategic leadership and data-driven decision making, Namita worked directly with the sales organization to optimize marketing campaigns and sales touch points, leading to the acquisition of new accounts and quarterly revenue growth. Outside of her role at Arista, Namita acted as a Mentor and eventually San Francisco South Bay Metro Director for the Cleantech Open, a clean technology startup accelerator that has helped over 1200 cleantech entrepreneurs to raise $1.2 billion and create over 3,000 clean economy jobs.

Namita first became interested in applying data to explore complex problems at McGill University, where she earned her BA in Economics and Environmental Studies. To explore her growing passion for blending data analysis and economic thinking with environmental problems, she accepted a position at Terrapin Bright Green, a boutique consultancy to corporations, real estate developers and other organizations seeking to answer the challenges of high-performance environmental design. At Terrapin, she was the primary author of The Economics of Biophilia: Why Designing with Nature in Mind Makes Financial Sense. This paper models the financial savings associated with building structures that give occupants sensory access to nature, on scales as varied as a single mid-size company, a state government and the national healthcare system. The Economics of Biophilia was quoted in the NYTimes, has been required staff reading at Interface Global, and has been used in coursework at Rutgers and Cornell.

Going forward, Namita is most interested in learning to use a diverse range of prescriptive and predictive modeling techniques, including linear regressions and machine learning techniques, within market research or user analytics to improve infrastructural and consumer products in the tech sector.

Liang (Leslie) Li

Leslie graduated from Beihang university and Politecnico di Torino with a B.S. and M.S. in Engineering. He used to intern at Intelligent Computing and Machine Learning Lab researching on Natural Language Processing. He devised an encoder-decoder neural network with attention mechanism, and the model is able to learn language mappings in a weak supervision way. His work got published on PACLING 2017.

After graduation, Leslie started his career as a data scientist in a startup in Beijing. He was responsible for the entire pipeline of Machine Learning work from data cleaning to model deployment and data visualization. He also cooperated with non-experts to interpret models and derive insights. He has done extensive industry data problems varying from recommendation to customer segmentation and successfully saved a great sum of money by adopting advanced analytical solutions.

Thrilled to be in MSBA 2018 cohort, Leslie aims to become a data professional by merging his academic and industry experience with cutting-edge analytical expertise. He especially hopes to excel in optimizing organizational effectiveness and outcome with data in varying business contexts.

Xin Li

Xin earned her Bachelor of Art in Statistics from University of International Business and Economics and is excited to dive deep into analytics through graduate studies. She believes in the power of using data to tell a good business story and looks forward to applying her knowledge in analytics and data science to business decisions.

Ada Lin

Ada Lin first developed an interest in data science as an undergraduate at Columbia University studying Economics, a discipline which combines quantitative analysis and social insights. Ada was particularly intrigued by the use of mathematical models to describe market dynamics and human behavior. During her senior year, she conducted independent research on the contemporary macroeconomic dynamics of Brazil. By consolidating data from various public sources, such as the World Bank, International Monetary Fund and Central Bank of Brazil, Ada built a model to predict the efficacy of inflation-combating policies in the country.

After graduating from Columbia, Ada started working at Forbes Media, where she gained relevant industry experience in business analytics. She was a Senior Analyst for the company’s digital branded content team. Ada was responsible for mining, analyzing and reporting on data related to the Forbes.com platform. Specifically, she sought to understand user behavior online in order to optimize the site’s performance and maximize digital advertising revenue. Her efforts contributed to a 93% growth in unique visitor’s year-over-year, as well as a 113% increase in native advertising clients. Additionally, she regularly worked cross-functionally with the sales, marketing and product teams to integrate data-driven efforts throughout the organization, proving to be technically proficient as well as possessing strong business acumen.

While attending Anderson’s MSBA program, Ada hopes to build upon the skills she developed throughout her academic and professional experiences to become a successful data scientist. She is particularly interested in how digital media companies gather and make use of big data availability to create algorithms that optimize product performance and tailor user experiences. Through instruction from world-class professors, exposure to top professionals in the field and hands-on experience digging into various projects. Ada will graduate the program with a better understanding of how to handle large datasets, create robust models and make sustainable business impacts.

Xuwen (Justin) Luo

Justin graduated from Nankai University with a major in international business, a combination of marketing, finance and economics. During his college time, he interned at investment banks such as CICC and market intelligence institutions such as Nielsen. His study at college offers him the ability to get business insights, and internship experience in different fields inspired his interest in applying big data analytics to business, especially finance industry.

After learning some statistics, finance and accounting courses, he started his first financial analytics program with Prof. Chu for a Chinese real estate giant. During this process, he got to know the impact of financial analytics for a company that helped a company allocate recourses, figure out key strategy and control operation risks. Therefore, he should deepen his business insights and acquire accurate data to draw more appropriate financial analytics. To accumulate his business experience, he interned at various financial institutions from commercial banks, investment banks to asset management companies. Everything was interesting, and he enjoyed the feeling to serve clients as well as learn new expertise, but he never forgot his original dream to apply big data to finance. And here at Anderson, he finally got the chance and time to learn advanced statistical and analytical knowledge. He looks for better chances to practice his analytical abilities in finance.

Qilan (Caroline) Ma

Qilan graduated with high distinction from University of Toronto in 2017 with a major in Statistics and a specialist in Financial Economics, a unique combination which equipped her with problem-solving ability and data-interpreting skills and cultivated her interest in data analytics.

Through her coursework, Qilan was dramatically intrigued with the process of mining and interpreting data and laid a solid foundation in probabilities and statistical theories. While accessing to data analysis in empirical studies and projects, she used regression models like OLS model and analyzed the accuracy of estimation by regression diagnostics. Meanwhile, she became well acquainted with software like R, Python and STATA to extract and analyze key information to solve real life problems.

Qilan also cherished the opportunity to apply the knowledge of analytics and sharpen her quantitative skills in data-driven business. In the internship in China Merchants Bank, she was responsible for credit investigation and credit line calculation. Using analytic theories and tools like Excel and credit risk management system, she conducted analysis on various financial data to explore its financial status and risks. She provided optimal analytic solutions to support decision-making process and finally contributed to the approval of a credit line with 15 million RMB. To gain a deeper insight into data analytics, Qilan interned as a data analyst in a software company after graduation. She collaborated in design of financial models for commercial banks’ credit risk evaluation system and helped them classify high-quality customers through data analysis and visualization by R and Tableau.

To embrace the era of Big Data, Qilan is thrilled to be enrolled in the MSBA program at UCLA Anderson. She hopes to arm herself with cutting-edge knowledge of data science and analytical techniques involving prescriptive modelling and machine learning, and cannot wait to become a professional data analyst who plays a pivotal role in effective decision making to improve the performance of data-driven business.

Xiaoran (Daniel) Ma

Xiaoran Graduated from Capital University of Economics and Business in 2017 with a Bachelor of Economics. He realized the power of analytics and its importance in present business industry during both his econometrics class and mathematical modeling contest. To improve his skillset and understanding of applied statistics, he took interns in both financial and media industries.

The broad application in statistics, widely use of data base and importance of business interpretation occurred frequently during his interns at Sohu.com. To better processing and reporting the data, Xiaoran created new searching method for mobile brand and related customer data in MySQL which decreased searching time by 90% and allowed automatic search and update. He updated and maintained auto report system with Xshell and Python. To satisfy the demand of different business developers, he self-leaned Python and provided customized up-to-date report to senior manager. Analyzing data and interpret the results was indispensable in today’s data-driven world. Weekly reports and explaining data to non-technical colleagues was part of his day to day responsibility.

With his keen interest in analytics, Xiaoran is now pursuing a degree in Master of Science in Business Analytics to consolidate his knowledge of applied statistics and programming as well as expand his understanding of data science to real industry projects. With the passion and experience, Xiaoran looks forward to achieving more and understanding more about technical complexities and its business applications.

Ankita Nagori

Ankita graduated from the University of Mumbai with a Bachelor of Engineering in Information Technology. For her final year project, she worked on time series modelling for sales forecasting and used data mining to increase the accuracy of the sales prediction by 15%. This sparked her interest in working with data. During her undergraduate studies, she had a good foundation laid in statistics and applied mathematics. Following her graduation, she accepted a position as an Application Developer at JP Morgan. She got an excellent opportunity to work on various projects where she could analyze and visualize data for risk reporting, product control and client notifications using technologies like Python and SQL. She has collaborated and worked with different stakeholders from across the globe like Japan, Australia, UK and US. She later decided to gain a deeper understanding of the predictive potential of data analytics. Fueled by her interest, she decided to pursue a master's in business analytics. During her coursework, she gained expertise in Prescriptive Analytics, Customer Analytics, Machine learning and Internet Analytics. This gave her a good platform to work with real-world applications and datasets. She later got an excellent opportunity to intern as a Data Scientist at BCG Digital Ventures. She accomplished working on different ventures and focused on sentiment analysis using natural language processing, loan default classification and dashboarding for Product and Marketing teams.Ankita has strong analytical skills and technical background. Her recent internship and previous work experience have helped her understand how to harness the potential of data to drive business decisions and add value to an organization.

Sherin Sebastian

Sherin graduated from New York University with a degree in Electrical Engineering. She then worked at Motorola Solutions as a pre-sale engineer and where she dealt with mission critical public safety infrastructure of New York City, Los Angeles County, San Diego County etc. While working closely with the sales organization at Motorola, she was exposed to the role of business analytics and how it is transforming businesses using data. Her fascination with understanding the impact of a data centric methods to drive business decisions inspired her to join MSBA program at UCLA, Anderson School of Management. She is particularly interested in understanding how we can use data to make knowledge driven decisions for both consumers and businesses in the digital age.  

She interned as a Data and Attribution intern at Snap Inc. for the measurement team within the revenue product department. She worked with user attribution and impression data to understand how various interactions on the app affect revenue. Her responsibilities included performing A|B testing using survey data, analyze current survey responses, measurement design, supporting audience generation for multi-cell resonance surveys, user attribution analysis etc. Working with very large scale datasets at Snapchat, helped her understand and learn various state of the art big data analysis techniques. Being part of the measurement team helped her gain extensive knowledge about how significant measurement is in the revenue and product growth for a company.  

Sherin intends to leverage the knowledge gained through the extensive curriculum at UCLA and her internship at Snap Inc. to develop her knowledge in causal inferences, internet analytics and machine learning. She is looking forward to new data frontiers and to grow her expertise as a business analyst.

Utkarsh Sharma

Utkarsh graduated from Jaypee University, India in 2013 with a B.Tech in Electronics and Communication Engineering. After graduating he worked with Cognizant Technology Solutions as a programmer analyst for 1.5 years. This was where he got proficient with programming languages like C and C++ and got good hands on experience in SQL.

After working in Cognizant, he decided to tend to his entrepreneurial spirit and started a gym and fitness center. He used his business acumen and strategy planning to establish his brand in the market. With his resilience and determination, he was able to successfully penetrate the market amongst the top competitors. He used his analytical thinking and skills to solve the problems his business was facing.

Also, while in his undergraduate days, he organized the first ever open street soccer tournament in Delhi and saw a participation of 128 teams. His skills in optimization techniques using MS excel came handy for smooth conduct of the tournament. Utkarsh has also worked as a part time mathematics teacher for students appearing for SAT.

Utkarsh’s keen interest in analytics and its application in businesses led him to pursue a Master’s degree at UCLA Anderson. He is interested in learning prescriptive and predictive analytics with focus on business strategy and looks forward to apply the knowledge he acquires at school to the projects he strongly believe in.

Furong (Fiona) Shen

Furong received both her Bachelor in Marketing and Master in Business Administration from Nanjing University, where she was trained to analyze business problems trough structured framework, understand consumer behavior in different market conditions with quantitative marketing research tools and gain a greater depth of understanding of their real-world application.

After graduating, Furong started at L’Oréal China as an Management Trainee. At this leading company in consumer products, she was extensively involved in online and offline marketing communication campaigns. Furong was immensely curious about what the target audiences want, what works, what doesn’t and why, and tried to use data to prove her insights throughout her job. She developed and executed digital marketing campaigns targeting young audiences by analyzing their media channel behavior and content preference, improving social media conversion rate by 10 times. To prepare for new work scope —crisis communication, she collected and synthesized data of historical crisis issues from media monitoring database for predictive modeling and made suggestion on media relation strategy.

Seeing the power of data analytics during her career gave Furong the passion and desire to further build on her skill set through the M.S. in Business Analytics program at UCLA Anderson. Furong is excited to learn from her cohort with various background and perspectives. She is keen to transform herself to a data expert in business context, turn her passion for data into strategic decisions and make the difference.

Cheng Tian

Cheng graduated from University of California, Santa Barbara with a degree in mathematical science and minor in Chinese. During his college time, he enjoyed in getting to know how to interpret data using statistics; solve differential equations and projects using numerical analysis; and build critical thinking ability. Of all the courses he took in university, he was most interested in applying analytical skills into real-life cases.

After graduation, he started his career at a healthcare strategy company, where he practiced his analytical skills by working on survey data. He found it both very interesting and rewarding to leverage his skills to process raw survey data and make them accessible for further analysis. For example, he Scanned, cleaned, and input survey data from over 1000 patients daily, and made analysis reports to clients and analytics team, enabling healthcare providers to improve level of care based on results and providing senior analysts with meaningful data for deep analysis. He also created excel tables to keep track of department performance to calculate and improve data accuracy. These wonderful experiences spark Cheng’s interests in data science.

Cheng is looking forward to enhancing analytic techniques related to computer programming and data visualization. Through MSBA program at UCLA Anderson, he is eager to improve his analytical and technical skills by learning the most cutting-edge machine learning methodologies and data science tools.

Hande Turkcapar

Prior to UCLA Anderson, Hande worked as an investment banking analyst at Credit Suisse, where she advised technology and emerging markets companies of various sizes on critical transactions.

She graduated cum laude from University of Chicago with a degree in Economics and holds a certificate in Software Product Management from Product School. She is fascinated by companies redefining data's role in creating software and mobile products that customers love.

Jiawei Wang

Born and raised in China, I graduated with distinction from Wuhan University, China in 2017 with a degree in Accounting and Finance. Four years of multi-discipline study and practices have equipped me with sharp business acumen, strong statistical and programming capacities, rich startup and internship experiences. Now I'm particularly passionate about leveraging data analytics to improve business operations with strategic decisions.

I first became fascinated by the application of analytics methods on business operation when I worked as a co-founder of a startup in the sophomore year, then I paid great attention to statistics and programming courses including MATLAB, SAS, probability theory, etc. Meanwhile, advanced course projects also equipped me with rich experiences in applying mathematics to business, e.g., using autoregressive integrated moving average model for stock price forecasting.

To enhance my data analysis and programming skills, I joined Morgan Stanley Capital International as an intern, there, I monitored parameters of portfolios with SQL and conducted analysis on portfolios using multi-factor models in various verticals. Furthermore, as a winter intern at Deloitte, I participated in 5 projects in 4 cities with 4 different project teams, implemented quantitative models in Excel to estimate potential misstatement risk and investigated the reason behind the variance.

To better combine my analytical skills with the understanding of various industries, I joined A.T.Kearney as a consultant assistant to help clients formulate optimal solutions with cost-efficiency higher than major competitors through processing and analyzing massive performance data by using R. Then I was totally fascinated by the process of analyzing large-scale data to make business decisions and started taking online courses to teach myself with Python, R, SQL and machine learning.

Driven by pure passion in the application of data analytics to optimize business decisions and solve real-world problems, I decided to pursue the Master’s degree in Business Analytics at UCLA Anderson. Through the program’s interdisciplinary curriculum in cutting-edge analytics techniques and hands-on corporate sponsored projects, I'm excited to dive in the data science and machine learning world and really hope to apply this knowledge in a business data scientist role in the data-driven future.

Shiqing (Stacey) Wang

Stacey comes from an engineering background and has worked 4+ years before she attended UCLA. She graduated from the University of Alberta with a master's degree in Chemical Engineering. 

She then joined Jacobs, a global leader in engineering consulting. Their main clients are oil producers, such as ExxonMobil, ConocoPhillips, and Shell. Her responsibilities include process data analysis, simulation and optimization. More specifically, she created SQL scripts and complex queries for data analysis and extraction, developed Python programs for data cleaning, and built process simulations and models for project debottlenecking, which helped clients solve engineering challenges and achieve their business goals. 

Stacey is currently a Data Science and Analytics Intern at Paramount Pictures. She worked in the Research & Analytics team in the Marketing Department. Her responsibilities include: building predictive models to forecast box office revenue, developing optimized marketing campaign strategies, performing audience segmentation, analyzing movie metadata to discover audience insights, and using data-driven actionable results to support publicity campaign and creative design. 

In the MSBA program, she enjoyed machine learning, prescriptive models, marketing analytics, customer analytics and web customer analytics. Her unique combination of engineering and business enabled her to solve problems logically and creatively. Her passion for data analytics drives her to dive deep into this area. Stacey looks forward to full-time opportunities where she can apply her knowledge and skills to help companies unlock insights from data and achieve business goals. 

Yidan Wang

Yidan Wang has a mixed background in both management consulting and data analytics. He has previous worked as a Data Analytics/Data Engineering Intern at Bain, McKinsey and TalkingData, China's top 1 mobile data firm. His job at TalkingData equipped him with solid skills in dealing with extremely large datasets under distributed computing frameworks (Hadoop, Spark) and using Python to implement data mining, feature engineering and various machine learning algorithms.

As an avid fan of functional programming, he is extremely proficient in Scala Collections, Spark APIs and had experience with mining 200 TB mobile device location data to detect patterns in billion-scale population migration. He has done impressed work by improving Compressed EWAH Bitmap’s functionality in Scala to store presence/absence info across different time frames and regions, which drastically improved the batch query processing time. Yidan has a solid background in mathematics and statistics. He studied Stochastic Processes, Regression Analysis and Applied Time Series during his exchange period to National University of Singapore and holds a Bachelor’s degree in Management Science and Engineering (Real Estate) from Central University of Finance and Economics.

Anbang (Brandon) Wu

Brandon is passionate about machine learning application and data production in media & entertainment industry, and is currently working part-time as a data science intern at RAPP Worldwide’s Los Angeles office. He has solid working experience of using R, Python, SQL, Tableau to help clients achieve various marketing objectives, and is excited about learning big data technology such as Hadoop, Hive & Spark at UCLA Anderson’s MSBA program.

Prior coming to Anderson, Brandon worked at a media & technology firm named Open Road Integrated Media in Downtown Manhattan, New York. He helped company evaluate campaign performance & effectiveness, achieve marketing channel optimization and reveal important insights into audience’s behavior.

Prior to Open Road, Brandon received his undergraduate degree from the University of Michigan’s Ross School of Business with majors in Technology & Finance and minor in Economics. He had extensive academic training in mathematics, statistics, programming and was fascinated by advanced analytics, machining learning, big data tools courses at his final year.

Di (Elva) Wu

Elva graduated from the University of Toronto with a double specialization in Finance & Economics and Management, and a minor in Psychology, a unique combination that made her a logical problem solver with a creative and people-focused mindset.

After graduation, Elva immediately applied her analytical skills to solve business challenges in various industries including E-commerce, Venture Capital, and Consulting. Elva first joined Rent Frock Repeat (RFR), the largest Canadian dress rental platform, where she helped RFR's marketing team improve social media content strategies. She leveraged data visualization tools like Tableau and statistical methods such as A/B testing to provide measurable suggestions to optimize Facebook content and ad strategy, leading to a 100% increase in click-through rate within 3 months. In order to see the big picture and gain a holistic understanding of business and company structures, Elva decided to stay in the Venture Capital industry as an analyst for 2 years, where she conducted financial, operational, and technical due diligence on 500+ companies from various aspects and angles, providing recommendations to help the investment committee make decisions on $22M worth of investment deals. With a solid analytical and research foundation, Elva later joined Merkle Inc., a leader in the performance marketing consulting industry, as a data specialist. At Merkle, she provided data-driven recommendations to help clients efficiently allocate marketing budget and improve sales and operations performance.  

On top of analytics, Elva also gained experience in data management & governance by working for the TechOps team at Kite Pharma, an LA-based pharmaceutical company. At Kite, Elva ran Data Audit cycle independently, at the same time enhanced the process to achieve broader coverage and higher-level of automation. She also provided best practice recommendations to Kite and developed a roadmap to bring Kite to world-class status in Data Governance.

Four years of working experienced helped Elva confirm her passion in business analytics. By pursuing a MS in Business Analytics at UCLA Anderson, Elva is further sharpening her data analytics skills, and cannot wait to apply those skills in her future career as a bridge between the analytics and executive teams, revealing the value embedded in data to drive better business decisions.

Jiaqi (Stan) Xu

Stan graduated from Fudan University in Shanghai, China with a bachelor's degree in Marketing Communication. Stan developed a strong passion for marketing analytics and customer analytics since then. He wants to create value for business entities and customers in this big-data era by truly understanding and using data.

Prior to UCLA, Stan embarked on a career in product management for Alibaba Group's AI product department. During his over two years working for the global Internet giant, Stan applied his customer analytics skills and developed several web and mobile products serving millions of users. 

He interned as a Business Analyst at Vineyard Vines this summer. He analyzed customer lifetime value from behavior and demographic data. As a result, he extracted actionable business plans on cross-channel marketing strategies and stores' location optimization.  

Stan is thrilled to join the M.S. Business Analytics program at UCLA Anderson. He hopes to continue refining his quantitative analysis skills, while developing his business acumen at Anderson, in order to help businesses and customers for the rest of his career.    

Ketong (Coco) Ye

Ketong (Coco) graduated from University of California, Los Angeles (UCLA) in March 2016 with a major in Business Economics and a minor in Accounting. During her time at UCLA, she was passionate about expanding her knowledge of regression models and hypothesis testing that could be applied towards analyzing economic phenomena and market trends. She supplemented her coursework by participating in case competitions and taking additional courses in programming and mathematics.

After graduating, Coco started as a tax consultant at Ernst & Young Financial Services Office. In addition to performing compliance services for multiple clients in Banking, Insurance and Capital Management industry, she also served as the tax subject-matter consultant who validated client’s financial securities data and tested the appropriateness of tax positions taken. At EY, Coco enjoyed learning new concepts, improving efficiencies of procedures, and thinking independently in a teamwork environment.

Coco is thrilled to be a part of the MSBA program where she can expand her knowledge in advanced analytics and data science. She is excited about the courses such as prescriptive modeling, competitive analytics, operations analytics and customer analytics. Coco is looking forward to applying the cutting-edge analytics techniques learned at the program to help companies make data-informed decisions and build competitive advantage.

Taotao (Tao) Ye

Tao graduated from Renmin University of China, where he majored in Human Resources Management. In addition to completing the coursework for his major, Tao also developed an interest in the use of quantitative methods to reveal insights from data and, consequently, devoted a lot of his undergraduate experience to studying statistics and math as well. For example, he participated in a study to analyze the emotional semantics of e-commerce platforms’ comments, during which he gathered knowledge about programming and algorithms.

Tao also leveraged his knowledge of analytics in various internships, where he supported the use of data-driven decision-making. In addition to developing daily reports, he also integrated his understanding of human resources and statistics to evaluate employee performance and developed strategies to augment the efficiency of workspaces. He also designed a program to collect information online in order to create reports that support various teams’ event planning initiatives.

The predominance of big data is changing the way both employees work and businesses function. Tao’s relevant research and internship experience enable him to understand the impact of big data and take advantage of it in the workspace. In the MSBA program at Anderson, he has been able to develop his knowledge of business analytics and apply his skills in solving real-world data problems. The sophisticated curriculum and experienced instructors from the MSBA program will further help him build a competitive advantage in the new era of big data.

Hang Yu

Hang's interest in applying data to solve real world problems began at Nankai University in China where Hang utilized a nationwide survey data to investigate the seemingly ambiguous effect of networks on entrepreneurship in China’s cultural settings. In this research led by two professors, Hang adopted logistics regression to identify the possibility of individual entrepreneurship in various institutional conditions and shared the findings in a peer-reviewed paper co-authored with two professors. Through this analytical experience Hang developed the ability to decompose complex puzzle into smaller questions and translate data into communicable conclusions. Hang was also inspired to explore more about analytics.

To keep up with this fast-growing enthusiasm, Hang interned as an analyst at a corporate group with over 30 subsidiaries in China. Using the financial performance data of each subsidiary, Hang applied lifecycle theory to classify the daughter companies. The lifecycle map of 30+ subsidiaries Hang drafted with other team members successfully convinced the executives of the corporate group to re-consider their development strategy for each business unit. During his internship at Accenture, Hang enhanced his communication and presentation skills by converting the analytical findings into strategy suggestions to client.

Hang is most interested in employing data to answer questions about customers. As a candidate in UCLA Anderson MSBA program, Hang hopes to sharpen his analytical mind-set and solidify his analytical toolkits in this dynamic environment. In the near future, Hang sees himself as a data analyst in the tech industry who transforms data into actionable insights for business.

Yizhe (Jonathan) Zhang

Jonathan graduated from Renmin University of China with a B.A. in Economics. Fascinated by the charm of econometrics and the big success from a data-driven project, he realized the vital role that quantitative analysis played in extracting knowledge, approximating truth, and developing a subject towards science. To improve his skillset as to lay a solid foundation for future analytics studies, he focused not only on the coursework but also learned more programming skills through online resources.

With the desire to step into the real business world and enhance his analytical skills through practice, Jonathan worked as an analyst intern at Nielsen. He used Tableau, Excel and R to clean and analyze a large set of data to engineer targeted internal marketing strategy for his client. During this process, he realized the tremendous value under those numbers and analysis in the business world.

After graduation, Jonathan worked as a full-time business intelligence intern at one of the top internet companies in China, during which he tried to utilize his technical and analytics skills to provide insightful strategies towards the company. He conducted a prescriptive model to analyze the impact of terrible weather towards the evaluation of delivery service on a daily-based dataset. He also built a k-means machine learning model to cluster different cities into 4 groups and made pricing strategy based on the clustering.

Driven by the passion in the application of data analytics to solve the real-world questions and optimize the business decision, Jonathan will strive to advance his analytics toolkits and accumulate more practical experience through the UCLA Anderson MSBA program. Especially charmed by machine learning, she believes that it will assist him with establishing better predictive models to provide optimal strategies for corporations.

Zhaobo (Will) Zhang

Bachelor of Science in Industrial Engineering, Shanghai Jiao Tong University
Master of Engineering in Logistic Engineering, Shanghai Jiao Tong University
Diplôme d'Ingénieur civil des mines, Ecole des Mines de Nancy

Born and raised in Shanghai, Will received his B.S. in Industrial Engineering from Shanghai Jiao Tong University in 2011. After entering the master program in Logistic Engineering at Shanghai Jiao Tong University, Will won a scholarship for a Joint Degree with Ecole des Mines de Nancy in France and graduated in 2015. Throughout his academic studies, Will has focused on statistics, operations research and optimization.

After graduation in 2015, Will started working for EY as a consultant focusing on financial risk management. At EY, Will handled large and complex databases and performed data visualization and financial risk analysis using VBA, SQL, R, and Python. He worked closely with his managing director in the context of the implementation of Basel III and financial innovation and transformation for financial institutions in China. During his tenure at EY Will had the opportunity to apply his solid engineering background and his quantitative skills to real-world cases. Based on the performance and clients’ positive feedbacks, he won twice the ExCEED award at EY. A key takeaway from his experience at EY was the importance of mining the data to retrieve and provide the most valuable and relevant insights and recommendations with clients.

By joining Anderson’s MSBA program, Will looks forward to improving his technical expertise, business acumen, and communication skills through coursework, industry projects, the summer internship and the capstone project. Please feel free to reach out to him if you seek any help on real business problems and data-driven recommendations to your business decisions.

Xuan (Sean) Zhong

Sean graduated from the University of California, San Diego with a B.S. in Mathematics/Computer Science. During his time in UCSD, Sean took programming courses which provided him with a solid technical background for his continuous study in Data Analytics. After he started the Business Analytics program at UCLA Anderson, Sean has found his Prescriptive Models and Machine Learning courses especially helpful with achieving his career goal of using data analytics to produce insights and solve real world problems.

Between school years, Sean completed internships in various roles across several industries. During his Sophomore year, Sean interned for a tech company focused on customer analysis where he wrote scripts to automatically collect and clean third-party data, which for the first time opened the door of data analytics for him. Before coming to UCLA Anderson, Sean interned at a financial consulting company as a financial analyst, where he analyzed financial data across deal sheets, built cash flow models and applied statistical simulations to produce credit scores that are much more accurate.

Beyond classrooms and offices, Sean also started his own business of reselling sneakers, where he acquired limited edition sneakers and sold them to clienteles both domestically and internationally. He was also able to use data analytics to mine the market and price data on different sneaker models and made optimal decisions on investing and selling.

Throughout his diverse experiences, Sean witnessed how data analytics played an essential role in everything that he had gone through. With both his passion and past experiences interacting with data, Sean is looking forward to apply his analytical skills on transforming columns of data into business insights and help elevating business performances onto a more optimal level.