Tianjia Chen

Product Analyst at Google | Ballet | Baking| Travel

WORK

Full-time

June 2019 - Present

Product Analyst, Android Security and Privacy Team

March 2018- August 2018

Product Analyst Manager, B2C Selling Team

  • Owned North America/Europe AB testing on important seller features.
  • Cooperated with PM Team, Data Engineer Team and Product Team on creating dashboards to monitor the behavior of seller registration& listing funnel.
  • Used cohort analysis to explore the performance of eBay third party tool.
  • Analysis and reporting automation with Teradata and Tableau.

July 2016- March 2018

Business Analyst,Business Intelligence and Strategy Team

  • Running organic A/B testing, including significance test, outlier removal, customer communication on test findings, etc.
  • Market research and industry reporting, including Year-over-Year Trend report, industry benchmark report, etc.
  • Analysis and reporting automation with Python(Jupyter), linux, AWS, excel.
  • Conduct a range of meetings and trainings within and across the teams.

Internships

To protect the information about companies, I did not put detailed information about projects here. If you are interested in it, feel free to contact me. Thanks! :-)

March 2015- May 2015    

Research Assistant, Institute of International Finance

  • Supported global economic research analyst with cleaned data, various data visualizations and topic-related materials.
  • Collected data from World Bank, OECD, Bloomberg and visualized through box plot, histogram, time series graphs, etc.
  • Created weekly International Financial Flash Reports. Worked on reports, including The Influence of Stronger Dollar to RMB Exchange Rate, Comparison of India & China Population, and also made contribution to Quarterly Banking Economic Report.

September 2014- March 2015    

Business Data Analyst Intern, Online Sales Group

  • Worked with team members to better promote products by implementing statistical modeling, visualization and statistical tools (with R, Excel, SAS, E-chart, SQL) to analyze online sales data.
  • Classified Intel online customers into 4 unique groups by Cluster Analysis.
  • Using Normal Distribution Rules enabled the team to concentrate on customers with unusual sales performance.
  • Predicted quarterly sales through a combination of Multivariate with Time Series Models under an error rate of 5%.
  • Created Gini Sales Index to monitor the distribution of sales data among old and new customers on a regular basis.
  • Visualized Intel APP customer behaviors through Heatmap, Survival Analysis, etc.
  • Appraised by Intel Headquarter manager for making presentations about data analysis projects on behalf of BI Intern groups.

Projects

New Haven Weather Prediction, Dec 2015

  • Keywords: Imbalanced Data; Logistic Regression; Boosting; Bagging.
  • Coding: R

Authors Classification Based on Corpus of Texts, Dec 2015

  • Keywords: High Dimensional Data; Logistic Regression with Elastic Net.
  • Coding: R

Classification of Benign and Harmful Substances, Dec 2015

  • Keywords: Principal Component Analysis; Multivariate Regression; Support Vector Machine.
  • Coding: R

A Delicious Recipe Analysis, Nov 2015

  • Keywords: Web Scraping; Text Analysis; Text Segmentation.
  • Coding: R

Study on Factors that Influence 2010 Boston Marathon Finish Time, Nov 2015

  • Keywords: Exploratory Data Analysis; Cluster Analysis; Multivariate Regression.
  • Coding: R

Twitter Sentiment Analysis, Sep 2015

  • Keywords: Text Mining; Twitter API.
  • Coding: Python

Real Estate Online Data Visualization, Sep 2015

  • Keywords: Web Scraping; Google API; Map Visualization.
  • Coding: R

 

 

Codings

R

Data Visualizations:

Bias in 2000 Olympic Games (package: Grid)

Algorithms:

An Example of Web Scraping

Coordinate Descent to Solve Elastic Net

Python

Online Courses:

Using Python to access Web Data, Duke University

  • Extract data from API, JSON, XML; follow links.

Using Databases with Python, University of Michigan

  • Writing SQL in Python; Relational Databases.

Machine Learning Foundation, Taiwan National University

  • Ridge regression, logistic regression with gradient descent.

 

Matlab

Online Courses:

Machine Learning, Stanford University

Java

Online Courses:

Java Programming: Solving problems with softwares, Duke University

Java Programming: Arrays, Lists, and Structured Data, Duke University

  • Array; Lists; ArrayList; HashMap; HashSet; Structured Data.

 

Javascript

Online Courses:

Programming and the Web for Beginners, Duke University