Data Analyst

SKILLS

Programming: & Software: SQL Python (Sklearn, Pandas, Numpy) Advanced Excel Tableau

Machine Learning: Classical & Penalized Regression Methods (Lasso, Ridge) Decision Tree Regularization Clustering KNN KMeans PCA

Statistics Analysis: A/B Testing Hypothesis Testing Time Series Analysis Forecasting Business Skill: Finance & Risk Management Market Research Marketing EDUCATION

Master of Science in Economics — University at Buffalo, SUNY, NY, 2013 - 2015 GPA 3.4 Bachelor of Science in Financial Engineering — Jilin University, China, 2009 - 2013 GPA 3.5 EXPERIENCE

Associate Financial Data Analyst, Verajoy Capital Real Estate, Redwood City, Nov.15 - Present

• Market and Property Research: Collaborating in acquisition of 6 properties, in total 174 mil- lion dollars. Evaluating value-add investment opportunities in residential and commercials prop- erties. Assembling and analyzing sales and rent comparables. Creating detailed market research reports to analyze economic state and real estate market trends to help decipher which markets will strengthen the company's portfolio

• Machine Learning Modeling: Implementing machine learning solution for house fairly value prediction and to predict or identify finance and investment related risks/opportunities. Scraping unstructured product listing data from website using Python Scrapy as needed

• Data Analysis: Writing optimized MySQL to query company databases and encoding business logic into key risk indicators for financial analytics model ingestion and visualization, highly recognized by Investor Relations for accuracy and presentation quality

• Financial Analysis: Analyzing profitability by designing and developing Excel Financial Mod- els templates: Pro-Forma Cash Flow Model, Equity Waterfall Model, Capital Cost Savings fore- casts, and preparing financial reports for investors

• Collaboration and Presentation: Using Tableau to create interactive dashboards boards and reports to identify product trends. Multi-functional in start-up and effectively collaborating with international partners and present bilingual (Mandarin and English) presentations PROJECTS

Kaggle Competition Top 8% — House Prices: Advanced Regression Techniques

• Developed algorithms to predict house price based on labeled data via Python programming and achieved top 8% accuracy in the competition

• Preprocessed data set by exploratory data analysis, data cleaning (outliers and missing values), feature engineering (datatype transforming, label encoding, Box Cox transforming)

• Trained supervised machine learning modelings, optimized by GridSearch, stacking and ensem- ble, and evaluated the model with best estimators in the test set SQL Project — DoorDash Delivery Operational Analysis

• Conducted analysis from demand (customer) and supply (restaurants and drivers), customer segmentation, logistic time segmentation, and order analysis (by city, time, schedule service)

• Performed fraud detection analysis with unbalanced dataset and evaluated tradeoff and cost SQL Project — E-Commerce Product and Sales Analysis

• Studied customer shopping pattern and provided growth and new customer acquisition insights

• Applied mySQL and Tableau to built visualized reports and dashboards and lead test outcomes

• Calculated monthly growth rate, forecast sales by product and store, correlated products, and site conversion rate

github.com/wentianma linkedin.com/in/wentian-ma San Jose 716-***-**** *****.**@*****.*** WENTIAN MA

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