Manager Data
Resume:
BINNY TSAI
ANALYTICS & DATA SCIENCE
CONTACT
! *****.****@*****.***
! Chino Hills, CA
" linkedin.com/in/binny-tsai
# github.com/tracy15932
EDUCATION
2017
UNIVERSITY OF CALIFORNIA, LOS ANGELES
B.S. in Math/Econ with
Minor in Stats
TECHNICAL SKILLS
§ Python, R, SQL (MySQL)
§ Pandas, NumPy, Matplotlib,
Seaborn, Scikit-learn
§ Apache Spark
§ Html/CSS/JavaScript
§ Linux, Bash
§ AWS (EC2, S3)
§ Machine Learning
§ JIRA, Git
§ Tableau
§ VS code, Spyder, Jupyter
Notebook
OTHER SKILLS
§ Languages: English, Mandarin
EXPERIENCE
Jan. 2020 – Current Los Angeles, CA
Insight Data Engineering Insight
§ Implemented a data pipeline by ingesting over 1.5TB/yr data with Spark and MySQL to create dashboard using Tableau to analyze news tone trend over period of time.
§ Helped investors and marketing teams to understand the global tone trend on news event in order to make more profitable decision.
Dec. 2019 – Apr.2019 Pasadena, CA
Junior Database Administrator OD International Investments Inc.
§ Performed troubleshooting, administration, and configuration on MySQL databases for a third party B2B online payment platform and a social educational platform.
§ Collaborated with team members to create database from QA to production stages and ensured robustness.
§ Managed user access priorities and security issues. Apr. 2018 – Aug. 2018 Taipei, Taiwan
Website Project Manager Intern DD Studio
§ Managed project schedules, tracked deliverables, and established priorities for the team.
§ Collaborated and negotiated with third-party software partners and internal teams to provide reliable solutions to client’s problems.
§ Created Gantt Diagram, Site-Map, and tested the web to resolve any rising problem on the function of the website.
§ Evaluated the trade-off for web development methodologies to improve overall performance by 30%.
Projects
# Salary Prediction Project
§ Predicted salary based on job features which can help HR department to improve recruitment process.
§ Used Python to manipulate about 1 million entries of data to perform data cleaning, visualization and analysis.
§ Developed machine learning models using Multiple Linear Regression, Random Forest, and Gradient Boosting to forecast the best compensation strategy by minimizing the Mean Squared Error (MSE).
§ Achieved an MSE from 470 at the baseline model to 357 under cross validation.
Monopoly Game Board Simulation Project
§ Used R to implement 1000 simulation of a two-player game and visualized the landing frequencies for each space with histogram to analyze the distribution.
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