Shuxiang Sui

New York, NY 484-***-**** ad2uzc@r.postjobfree.com www.linkedin.com/in/daniel-sui/ www.github.com/DanielS707 EDUCATION

Columbia University GPA: 4.0/4.0 New York, NY

M.A. in Quantitative Methods in the Social Sciences, Data Science & Behavioral Science Focus Sept 2022 – Dec 2023

Relevant coursework: Machine Learning, Data Analytics, Time Series, Database, Business Analytics, Modern Data Structure, Data Visualization, Natural Language Processing, Behavioral Economics. Purdue University GPA: 3.7/4.0 West Lafayette, IN

B.S. in Economics, Data Analytics Concentration, Management Minor Aug 2018 – May 2022

Relevant coursework: Advanced Econometrics, Advanced Spreadsheet Modeling & Simulation, Data Analytics, Microeconomics, Macroeconomics, Six Sigma & Quality Control, Predictive Analytics, Operations Management. PROFESSIONAL EXPERIENCE & PROJECTS

Consumer Financial Protection Bureau New York, NY

Credit Card Data Student Analyst (Python, SQL, Power BI, Miro, Excel) Aug 2023 – Present

Developed and implemented Python programs to explore and filter 70k+ raw datasets from CFPB, enhancing data usability.

Designed and executed 10+ behavioral science tests to classify user credit card habits, contributing to user segmentation.

Created 40+ MaxDiff logics offering 5 credit card recommendations through 400+ credit card benefit analysis & user research.

Collaborated with team members to align projects with the needs of CFPB, user advocates, and Subject Matter Experts (SMEs). Guzman Energy New York, NY

Quantitative Analysis Summer Project (Github, Python, Power BI, EDA, Excel) May 2023 - Jun 2023

Analyzed consumer electricity consumption behaviors from different time patterns and conducted exploratory data analysis

(EDA) for raw data with 10+ improvements in nudge behaviors and game theory model applications.

Created Python program that can automatically organize, clean, and generate visualized electricity consumption outputs built on different time and geographical units from massive unprocessed dataset.

Established time series forecast models to predict real-time local marginal energy prices for better bidding strategies, successfully reducing the Mean Squared Error (MSE) by 15%. Beijing NetSwift Tech LLC. Beijing, China

Data Analyst Intern (Python Jupyter, Excel, Tableau, Access) May 2021 – Jul 2021

Forecasted shortage’s impact with SimQuick and generated pivot table reports to assist company’s new product strategies.

Conducted chip turnover factor analysis with Pandas/Numpy and OLS regressions in Python; Carried out simulation reports with Risk from Excel and visualized most important potential factors that boost turnover rate.

Defined North Star metrics to measure the success of marketing campaigns. Built a series of Tableau dashboards to track key metrics, providing longitudinal clarity for leadership and influencing their product updating decisions. Xiaomi Corporation Beijing, China

Supply Chain Management Data Analyst Intern (Python Jupyter, Excel, Access, Xmind) Sept. 2020 – Dec. 2020

Leveraged advanced Excel functionalities, including VLOOKUP/XLOOKUP and PivotTables, to optimize inventory demand analytics across dealers and retail outlets, achieving a 12% boost in daily stock delivery efficiency.

Constructed comprehensive last-mile cost dataset for 35 retail stores in Beijing, ensuring detailed insights for cost management.

Implemented 500 statistical simulations using SimQuick (Excel) to gauge average and variability in last-mile time and labor costs, providing pivotal data for supply chain efficiency improvements. RESEARCH & TEACHING EXPERIENCE

Columbia University New York, NY

Enhanced Teaching Assistant II for Time Series, Panel Data & Forecasting (Python, R, Stata) Aug 2023 - Present

Led the time series labs, held weekly recitations, and coached 60+ master’s students in time series. Purdue University, Daniels School of Business West Lafayette, IN Economic Research Assistant (Python, Stata, R, Excel, Tableau) Aug 2021 – Jan 2022

Investigated 40k+ Germany gas station pricing strategies in the presence of AI algorithmic pricing and data transparency; collected, processed, and cleaned raw data into 50+ excel files; recorded abnormal data with 6 potential hypotheses.

Utilized time series and linear regression to analyze oil price data and identify pricing strategy variances; applied Lasso for variable selection and tested models using vectorized dummies based on demand. TECHNICAL SKILLS

Analytical Skills: Six sigma & Quality, Simultaneous, Probability, Operations Management, Machine Learning. Software Skills: GitHub, Excel(Vlookup/Xlookup/Pivot table/VBA), Access, Tableau, Google Analytics 4, Xmind. Programming Skills: SQL, Python, Stata, R, HTML, AWS.