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Data Scientist

San Diego, California, 92092, United States
January 24, 2017

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* ******* **. # ******, ** Jolla, California, 92092

917-***-**** EDUCATION

Columbia University Sep. 2015-Dec. 2016

M.A. in Statistics Overall GPA: 3.8 New York, NY Relevant Courses: Data Mining, Statistical Machine Learning, Applied Data Science, Linear Regression, Non- parametric Statistics, Bayesian Model for Machine Learning, Advanced Data Analysis Beijing Institute of Technology Sep. 2011-Jul. 2015 B.S. in Automation (Electrical Engineering) Overall GPA: 86.22/100 Beijing, China Relevant Courses: Calculus, C Programming, C++ Programming, Statistics, Data Structure B.A. in Economics Overall GPA: 83.35/100 Beijing, China PROFESSIONAL EXPERIENCE

SNAPWIZ INC. Jun. 2016-Aug. 2016

Data Science Intern Fremont, CA

Designed new features for an applicant tracking system named Glider in Python, using Natural Language Pro- cessing. (Click to see Glider)

Analyzed text data and implemented data-based algorithms to automatically score and sort candidates with better alignment to the job.

Maintained a web crawler for extracting resumes and job postings. Established a MongoDB database for crawled data.

Built analytic dashboards and unit tests in shell scripts to monitor the real-time performance of system. CITIBANK (CHINA) CO., LTD Aug. 2014

Summer Intern Beijing, China

Developed a survey website for research on Chinese attitudes towards Citibank nancial products, using HTML.

Wrote an analysis report about the impacts of Internet nancial products on traditional banks through modeling and data visualization.


Mining Amazon Movie Reviews Apr. 2016

Course Project New York, NY

Leveraged Social Network Analysis to provide movie recommendation by distance matrix.

Developed a Web App to recommend Oscar movies for users by their favorite genre.(Click to see the App) Cats versus Dogs Image Classi cation Mar. 2016

Course Project New York, NY

Extracted and selected features from 70K images by OpenCV.

Trained and evaluated more than 6 classi ers including Random Forest, AdaBoost and SVM.

Increased the classi cation accuracy by 17%, which ranked No.1 among 16 teams. Barglary Feb. 2016

Project Leader New York, NY

Developed a Shiny application to present crime statistics in NYC through choropleth mapping.

Designed a recommendation engine for safe bars via analyzing more than 20 million crime records. RecSys Challenge 2015 Mar. 2015-Jun. 2015

Individual Project Beijing, China

Predicted user online purchase behavior based on over 1.5 million click events and purchase events.

Reached over 97 percent prediction accuracy and ranked as 11th in the world. TECHNICAL SKILLS

Computer Languages R, Python, SAS, C, C++, Java

Database MongoDB, PostgreSQL, MySQL

Web Technologies & Tools Shiny, JavaScript, JSON, HTML, CSS Platforms & Libraries AWS, Azure, D3, OpenCV

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