Qinghuai (Michelle) Tan

Irvine, California P: +510******* adsjxa@r.postjobfree.com

EDUCATION

University of Chicago Chicago, IL

Master of Science in Analytics Expected Dec 2022

Relevant Coursework: Programming for Analytics, Time Series Analysis and Forecasting, Statistical Analysis, Data Mining Principles, Machine Learning and Predictive Analytics, Data Visualization Techniques University of California, Berkely Berkeley, CA

Bachelor of Economics Sep 2017 - May 2020

Relevant Coursework: Computational Structure in Data Science, Introduction to Probability and Statistics WORK EXPERIENCE

SAN FRANCISCO HOUSING COALITION San Francisco, CA

Research and Analyst Intern May 2020 – September 2020

● Utilized Salesforce to match up 200+ financial transactions of inflow and outflow funds. Boost efficiency by 15% through building data pipelines and automating manual Excel processes of financial records merging from the year 2018 to 2020.

● Redesigned the analytical visualization dashboards, such as housing market patterns, for web pages contents renewal using Excel and Tableau. Translated more than 20+ company web pages into Mandarin for future Chinese Clients’ usage. Reached an estimation of increasing website engagement time by 20%.

● Contributed to market research and conducted 5+ project reports to support company’s advocacy on behalf of pro-housing ballot measures.

Phoenix Finance New York, NY

Financial Research Intern May 2018 – July 2018

● Assisted Chinese office’s IPO launch by preparing 5+ research analysis reports by reviewing 30+ market reports on introductory technical references, including topics on Robo-advisory, block chain.

● Participated in initiating financial portfolios on companies in a 5-members’ team by collecting stocks, bonds, commodities, and exchange traded funds’ information on open online financial databases.

● Synthesized the analytical and graphical results into 8+ case presentations for bi-weekly team conferences. PROJECTS

CREDIT CARD FRAUDULENT DETECTION PREDICTION (Python) Nov 2021

● Processed 28k rows of credit card transaction data in Python, applied SMOTE for oversampling to achieve balance data, and performed exploratory data analysis for further feature engineering and data standardization in a 4-person team.

● Built multiple machine learning models including logistic Regression, SVM, Keras Model, Random Forest to predict fraudulent transactions and reach 0.89 precision score.

● Applied the model into real-world practice based on the business case and increased the value estimation of the credit card market from the current revenue state of 3.4 Billion to 6.7 Billion. TORONTO BIKE SHARE USAGE ANALYST (SQL & Python & Tableau) Nov 2021

● Used MySQL to select, sort, rearrange and analyze data among 6 databases collected from the official website for the City of Toronto. Built Enhanced Entity Relationship (EER) models and dimension table among databases within MySQL.

● Performed exploratory data analysis for over 200K rows of bike-share data and identified key factors influencing bike share usage through correlation analysis, including ridership, customer segments, using date, covid-19-cases distribution, neighborhood crime rate and weather records.

● Utilized Tableau to build more than 10 dashboard views to demonstrate dynamic data summary and analytics results. Gave business strategies of an estimation for bike-share system’s efficiency improvement by 20% and cost reduction of 30%. ADDITIONAL

Technical Skills: Python (Numpy, Pandas, ScikitLearn, Matplotlib), R, SQL, MongoDB, Spark, Hadoop, Hive, Tableau Statistical Analysis: Data Distribution, Correlation, A/B testing, Statistical Inference, ANOVA Machine Learning: K-means Clustering, Linear/Logistic Regression, SVM, KNN, Decision Tree, Random Forest

Contact this candidate