Data Analyst

QIAN TANG

Email: **************@*****.*** Phone: +1-530-***-**** LinkedIn: Qian(Tia) Tang

EDUCATION & CERTIFICATION

University of California Davis (UCD) 2017 – 2019

M.S. in Statistics, expected June 2019 (GPA:3.76/4.0)

• Programming Coursework: Data Structures, Algorithm Design, Database Systems, Theory Computation

• Statistics Coursework: Stat Methods For Resch, Probability Theory, Stat Methods And Models Jilin University, Changchun, China 2012 – 2016

B.S. in Information and Computing Science (GPA:3.76/4.0) -- Major B.S. in Insurance (Actual Science) (GPA:3.54/4.0) -- Minor

“Managing Big Data with MySQL” from Coursera

“Data Analysis with Pandas and Python” from Udemy

SKILLS

Technical: MySQL, Python(Numpy, Pandas, SKlearn), Teradata, R(ggplot2, random forest, markdown), Tableau, Excel(Pivot Table), LaTeX, MATLAB

HONORS & AWARDS

Outstanding Student Award, Jilin University First Academic Scholarship, Jilin University WORK EXPERIENCE

Data Analyst at Epidemic Disease Prevention Center, Jining, China Sept 2016 – Jan 2017 Retrieved, consolidated, analyzed and summarized data from very large data sets using MySQL and Microsoft Excel. Analyzed claims data to assess program performance and to identify any issues, trends and opportunities for growth. Produced reports for and interface with senior management and internal and external stakeholders.

Financial Analyst Intern at AXA, Hong Kong, China Sept 2015 – Nov 2015 Conducted a comprehensive analysis of stock market index to define stock evaluation models and generate well-grounded recommendations for fund creation. Optimized the company’s portfolio by implementing CVaR model in MATLAB effectively. Prepared and delivered investor reports and presentations. RESEARCH EXPERIENCE

iOS Instagram App Winter 2019

Developed an iOS Instagram application employing Swift and Firebase. Created account and managed profile data which is stored in SQL Database. Utilized Firebase Cloud Messaging to send users a notification of a new follower. Uploaded photos to Firebase Storage, retrieved their location URL, and stored them inside of Firebase Database to share posts. Added a like for each post in Firebase Database. Predict Future Sales Winter 2018

Entered top 11% at Kaggle competition. Applied machine learning algorithms to predict next-month product/store sales for 1C Company, one of the largest Russian software firms. Manipulated various types of values to conduct data cleaning, missing data processing. Exploited my xgboost and times-series data skills and achieved impressive root mean squared error (RMSE) at 0.90646. Toxic Comment Classification Spring 2018

Applied machine learning algorithms to deliver multi-headed models. Converted a collection of comment texts to a matrix of TF-IDF features for feature extraction. Achieved 97% accuracy through a multiple Logistic Regression model and 3-fold cross-validation. Improved the accuracy to 98% by using a CNN model. House Price Prediction Spring 2018

Built a house price prediction model with 79 explanatory describing every aspect of residential homes in Ames, Iowa. Analyzed the most correlated variables and dealt with missing data and outliers. Extracted key features in big messy data via multiplied methods in feature engineering. Employed lasso regression, gradient boosting and achieved test error at 0.083 through 10-fold cross validation.

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