2019 Interns

Jay Li

Jay Li, Data Scientist Intern, Texas Health Resources

“In this summer, I have been afforded the unique opportunity to work as Data Scientist intern in the Texas hospital, Texas Health Resources. I was responsible for consumer segmentation project that I built up machine learning pipeline to categorize consumers based on their demographics and behavior data. The project has produced profitable results that I introduced the new powerful features and created interactive dashboards in Tableau to derive consumer insights and patterns, which support business decisions and tailor marketing effort. It was a very meaningful experience because the 10-week internship program honed my interpersonal skills to solve real-world problems, and also the ability to tell good stories behind data to non-technical personnel.”

Alexandra DeKinder

Alexandra DeKinder, Intern, Columbia Care

“I worked with the data team to streamline analysis projects and generate data reports. I accessed data from their new AWS data lake to create data visualizations for different company reports. I also helped guide new analysis angles and worked with both internal and external parties on different projects. The statistical computing classes offered in the MA Statistics program, as well as the career development opportunities, were critical to my success in this internship.”

2018 Interns

Mathieu Sauterey	Mathieu Sauterey, Quantitative Investment Intern, Varadero Capital “I supported the investment research effort of the firm by helping my team develop a credit analysis tool. The purpose of this tool was to gain additional insight on the pricing of loan coupons, on a risk adjusted basis. Thanks to the quality of the MA Statistics program and the excellence of my internship mentors, I was well prepared to work on this project which entailed writing SQL scripts and building machine learning models in R. Additionally, my team and I used Tableau to visualize our findings and we successfully delivered clear credit investment recommendations to higher management.”
Atishay Sehgal	Atishay Sehgal, Data Fellow (The City of New York) “This summer, I worked at the Staten Island Borough President’s Office as their sole Data Scientist. I worked on a few projects including evaluation of a Randomized Control Trial – assessing the effect of cardiovascular exercise on academic outcomes on Staten Island, making a case for affordable housing for senior residents of Staten Island, evaluation of the rollout of the MTA’s new express bus service and other small projects. Each of the projects included the use of R extensively, Statistical Inference, Machine Learning and Data Visualization in RShiny. We published our findings on RPubs too.”
Scott Szatkowski	Scott Szatkowski, Intern, DRW Holdings “As a Risk Analyst Intern at DRW I worked directly with Senior Risk Managers to develop two network-hosted R Shiny applications which identified financial behaviors of interest. The first identified abnormal patterns in LIBOR and OIS term rate curves for several currencies and the second analyzed patterns in implied volatility surfaces for treasury options, commodity futures options, and index options. I also aided in writing an option pricing tool for the desk’s central risk program and reviewed the group’s historical interest rate derivative databases to classify unreliable data.”

2017 Interns

Hongyu Ji	Hongyu Ji, Intern, Volkswagen Finance “As a risk management intern at Volkswagen Finance, I helped the team complete a project which targeted a reduction in financial loan losses and maximization of profits. My main job was to utilize R and SPSS to determine which variables have most predictive influence through some predictive modeling in order to improve the efficiency of reviewing customers’ files to decide if they can get a loan. Also, I used BI and Excel to summarize significant features from different auto finance loans banks and car companies to know how competitive our company is in the society.”
Song Lu	Song Lu, Risk management Trainee, J Greenman Consulting “I completed two projects during the summer. First, I initiated a framework for scorecards in cyber security and built parameters to quantify cyber risk. Second, I assisted in the product development process of a CRO Reporting Framework which covered capital positions and capital action plan under CCAR, KRIs such as LCR, NSFR and Return on RWA under BASEL III to measure bank’s profitability, liquidity, valuation.”
Sean Reddy	Sean Reddy, Intern, Capital One “This past summer I delved into computer vision as part of Capital One’s Tech Innovation/R&D team. I developed and implemented an end-to-end solution for: a) real-time object detection of cars present in an image/video feed and b) identifying these vehicles’ makes and models in a variety of conditions present in the real world. We ultimately built a fully functional mobile prototype with ~95% accuracy on over 400 different cars, including augmented reality components added by fellow members of the R&D team.”
Xueyang Wang	Xueyang Wang, Accenture “At Accenture, I got enrolled in a strategic consulting project with a very tight timeline within one month. We initiated a whole package of launch plan for a 12 km² health science industrial park. In a team of only 4 full-time consultants, I almost facilitated in every step down the road from very scratch. We conducted landscape analysis to understand the broad context on different sub-industries in health science by secondary research and primary research (IDIs, focus groups & online surveys). Further on, we prioritized industry entry and assessed their value proposition based on competitive benchmarking, policy review and customer segmentation.”
Qinyuan (Amanda) Zhang	Qinyuan (Amanda) Zhang, Statistics, Data Science and Engineering Intern, Autodesk “I was responsible for developing an A/B testing algorithm which can be applied at scale for all products from the company. The idea of the project was to enable data-driven decision framework for the stakeholders and efficiently evaluate the performance of an ongoing project. As the only intern with statistics background, my project matched perfectly with my skillset and filled the gap of lacking statistical support in the team.”
Chenyun Zhu	Chenyun Zhu, Intern, MongoDB “I was given ownership of a project which aimed to critically evaluate the performance of MongoDB’s global sales organization. My main responsibility was to implement predictive modeling techniques to forecast seller performance in order to help make the data-driven management decision. In addition, I collaborated with finance team to analyze ramp time and attrition of sales team in different market cohorts. My daily tasks included meeting with different teams, creating scripts in R to achieve data automation, statistical modeling.”

2016 Interns

Minghao Dai	Minghao Dai, data analyst, Ipsos “Most of my daily work was cleaning and analyzing data sets related to healthcare. I used R most of the time, extracted the relevant information from the data and then arranged them in a more clear way. I also did hypothesis testing, regression and prediction with the data. In general, I think my statistical knowledge and coding skills are the two essential parts of my internship.”
Daitong Li	Daitong Li, summer intern, Gooroo “I spent the summer interning at Gooroo, a fast-paced education technology start-up offering on-demand tutoring service. I joined the business development team where I worked creatively on digital marketing campaigns. Moreover, I offered tutoring and consulting services to clients on various statistics courses and projects. I found the internship through the department weekly email, it linked me with the resources and contacts I was looking for.”
Lu Zhang	Lu Zhang, intern, Compass “My job included pricing/valuation of selected condos and coops, analysis of rental and sales data and management of ownership database. I got familiar with the real estate market in the midtown and downtown Manhattan as well as Williamsburg in Brooklyn. It was exciting!”
Eric Zhang	Eric Zhang, data scientist, Johnson & Johnson “I was a member of a special group in the J&J IT Application Services division called DataLabs, which focused on fast prototyping of machine learning/data science/analytics solutions to problems in the healthcare technology space. We received work requests from various business units within J&J, and then given a set of data and project requirements, we determined the best way to attack the problem and then built a proof of concept solution in 3 weeks using a variety of tools (including R, Python, and Tableau). We essentially functioned as internal consultants for the wider organization, where we were paid to deliver specific analyses to managers and directors in other J&J departments. My role in each project was a combination of data gathering/cleaning, analysis, visualization, and demoing/pitching to the client each week.”
Yunyi Zhang	Yunyi Zhang, intern, Quantitative Equity Research Department, Delaware Investments “My daily job was related to factor analysis, portfolio attribution and backtesting. I also presented the results of our research to other investment teams, wrote reports and automated some models and functions we developed. Statistics background provided me with a quantitative perspective when viewing financial issues and great ideas in constructing and examining models.”
Chi Zhi	Chi Zhi, quantitative research intern, OmniMarkets “I participated in developing an application by which investors could access to multiple consumer lending platforms and choose assets picked up by underlying algorithms to invest. I did most of the back-end work, including data collection, database schema design, and algorithm development. I enjoyed and learned a lot from it.”
Nisha Khilnani	Nisha Khilnani, marketing analytics intern, Experian Consumer Services “On a day-to-day basis, I extracted data using SQL Redshift, performed statistical analyses through SAS, and also developed and maintained weekly reports through MS Excel. These analyses consisted of a variety of topics, from analyzing marketing campaign efficiency, to understanding and identifying correlations between survey data responses, and membership subscription activity. My capstone project towards the end delved deeper into our Salesforce data and internal subscription data. The goal was to identify High Quality Engagements (or activities that led to conversions) within our call centers, online links, and email marketing efforts using statistical techniques. During my last week at Experian, I was given the opportunity to present this analysis to several executives, including the Chief Marketing Officer, the VP of Digital Marketing, and the Senior Director of Ad Operations and Analytics. This overall experience allowed me to use statistical methods learned in our courses here at Columbia, as well as gain additional skills, such as marketing strategies and communicating to individuals outside of the statistical realm.”
Yuhan Sun	Yuhan Sun, Data Analyst Intern, UNICEF (United Nations Children’s Fund) “My job involves two parts. One is to upgrade the Child-Mortality Estimation Shiny App and help develop the IMR Shiny App. Another one is to support the data analysis and visualization of a report on refugee and migrant children which is for the 71st General Assembly. R (especially Shiny), Tableau, javascript were the main tools I used in my work. This internship was a perfect match for my background.”