Zilong Li

1. Forecasting: apply advanced modeling techniques to forecast the topline business metrics such as demand, supply, ride volume, and the key financials such as bookings, net revenue, and profits 2. Strategic plannings: utilize the forecasted outputs to help leadership set short-term and long-term business goals, and make investment decisions on both rider and driver side to ensure the overall market balance and business growth 3. Focus area: rider engagement, rider acquisition

Leverage advanced data analytic techniques to consistently track and monitor the rideshare business performance

• Led the migration from VBA-dictated option pricing system to the fully automated python platform, resulting in significant efficiency improvement • Designed and maintained an integrated data infrastructure including a real-time data pipeline, various data preprocess, and interactive data visualization, reducing regular derivative pricing work load by 30% daily • Developed alternative flexible settlement methods with advanced statistical modeling and machine learning skills, which leads to less financial model dependency

• Conduct data preprocessing from disparate sources with advanced Oracle SQL query techniques • Developed an interactive Python validating GUI to automate and simplify the downstream model validation process, improving the task efficiency by 20% on average • Built various supervised/unsupervised statistical models to estimate the intrinsic values of illiquid/non-public assets, further diversifying and improving clients’ portfolios performance

*Conducting statistical analyses on topics related to early childhood education using SPSS/SAS/STATA/R; *Applying various regression models and data mining analytics on both cross-section and longitudinal samples; * Participating in the whole statistical analysis process including data cleaning, modeling, testing, troubleshooting, and final report writing and editing.

two-year full-time academic program in statistics, specifically focusing on the financial statistics and risk management area. Staring this Spring term, I will begin to receive formal training in graduate-level statistic knowledge, including several required courses, such as "probability and statistics"​, "regression analysis"​, "design of experiments"​, "interpretation data"​, and "method of statistical inference"​, "data mining"​, "advanced programming in statistical analysis"​. Some optional courses also include "foundations of risk management"​, "algorithm"​, "machine learning" etc. Among these two years, I will be expected to learn at least 10-courses plus a final project towards the final MS master degree.