SISONG(BENNETT) BEI

New York, NY 831-***-**** adhitc@r.postjobfree.com www.linkedin.com/in/bennettbei198222133 TECHNICAL SKILLS

• Statistical Skills: R, Python, MATLAB, Excel Analysis, Stata, SQL

• Visualization Skills: Tableau, R, Spotfire, Alteryx, Bloomberg Terminal

• Machine Learning Skills: Big Data (Hadoop, Spark), Deep Learning (AWS), Python/SPSS Modeler (regression, classification, cluster, etc.), Text Analytic EDUCATION

FORDHAM UNIVERSITY, GABELLI SCHOOL OF BUSINESS New York, NY MS, Business Analytics, Expected Dec. 202*-****-****

• Relevant Coursework: Database Management, Deep Machine Learning, Web Analytics, Big Data UNIVERSITY OF CALIFORNIA SANTA CRUZ Santa Cruz, CA Bachelor of Science, Economics/Mathematics 2015-2018

• Relevant Coursework: Econometrics, Real Analysis, Probability Theory

• Management Science, E-commerce, Corporate Finance

• Stevenson College Dean’s Scholarship

• Vice President of Chinese Students &Scholars Association, Mathematical Research Department EXPERIENCE

FORDHAM UNIVERSITY, GABELLI SCHOOL OF BUSINESS Spring 2020 Technical Member - Analytics/Data Science, Design Lab, Center for Digital Transformation

• Use coding skills to collect, merge, and preprocess datasets ready for regression

• Built smart contract with Node.js and Markov Decision Process Toolbox for market simulation AGRICULTURE BANK OF CHINA Summer 2017

Financial Analyst Intern

• Performed AR, MA and Random Forest models with higher than 75% accuracy to evaluate financial statements and then analyzed sales costs, expenses and revenues

• Prepared detailed spreadsheets to develop forecasts and summarized recommendations on ROI to accumulated 7 clients

PROJECTS

DELOITTE NCAA MARCH MADNESS DATA MINING COMPETITION Spring, 2020

• Merged all relevant preseason game data of each team and use machine learning technique (Random Forest, KNN, Naïve Bayes) to predict probability of each game would win the tournament SEC DISCLOSURES SUSTAINABILITY ANALYSIS Summer, 2020

• Collected the environment disclosures from companies 10K reports with python scraping code

• Perform sentiment analysis and topic model to generate insights and labels for companies

• Merged ESG and financial data from Bloomberg and using machine learning models to test association BIG DATA- USER EXPERIENCE PREDICTION AND RECOMMENDATION SYSTEM Spring, 2020

• Collected 5.7 million reviews and 800 thousand user data from yelp and processed with Spark on GCP

• Build LSTM model to predict users’ satisfaction and adjust recommendation system ADDITIONAL

• Languages: Chinese(native), English(fluent), Japanese (intermediate)

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