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JUSTIN TSENG GREENCARD HOLDER

adcgjg@r.postjobfree.com +1-347-***-**** New York City hualai-tseng-justin/ hakunamatata9981 SUMMARY

A data scientist passionate about solving new business problems by applying data-driven approaches, and is capable to communicate by simplifying complicated ideas.

EXPERIENCE

Data Scientist - Fellow, Springboard, New York City May 2019 - Current Hands-on experience with statistical inference and machine learning techniques through courses hosted by Harvard in this curriculum. Experienced with data visualization and storytelling while upholding the integrity of interpretation in highest regards. Analyst Intern, Emerging Strategy, Shanghai Dec. 2017 - Mar. 2018 Give insights to international educational service for the Chinese market by data collecting, visualizing and group discussion, then interpreting the research result with recommendations for our client. Researched and analyzed datasets related to automotive and other service industries. Extracted solutions from the gathered data, utilized Excel and Powerpoint to present visualized data and modified strategies during clients’ meetings and restructured research methodologies to achieve client’s scopes.

Research Analyst, Shenzhen Field Investment Co., Shenzhen Oct. 2016 - Dec. 2017 Brainstorm and design investment plans to help investors make decisions on a multi-million dollar investment on Tokyo's properties market by analyzing data and notes gathered from property agencies, industry experts and Google research. Help a luxury travel brand to boost their workers' efficiency by creating a production chain. By analyzing records of workers' progress and performance, the recorded data not only help prevent risk but also increase customer reviews and loyalties. Collect investors' data and perform risk assessments to help select candidates for each fund pool after obtaining designation as a Qualified Fund Worker through the Asset Management Associate of China (AMAC). Social Media Platform Analyst, Taiwan Legislative Election, Taiwan July 2011 - Jan. 2012 Utilized statistics data generated by Facebook to map out the best online marketing strategies for the candidate, for example by posting pivot advertisements primarily on Tuesday mornings. We found data showed that this time window would engage the largest number of working professionals based on their social media habits. After target marketing for two months, we quadruple our candidate's popularity. Promoted a manifesto for childcare by designing a Christmas project to boost support for the candidate among women. Because of this initiative, not only did the polling data revealed significant growth in interest from female voters, but it also had presses broadcast on national TV.

PROJECTS

NYC Housing Price Prediction Oct. 2019 - Current

To predict the future housing market in NYC, I applied regression models and obtain an R^2 score of 26% for continuous target variables ranging from 0 to 4 billion USD. Currently working on aggregating data for time series analysis to test if a different approach can help improve the result. Credit Card Fraud Transaction Detection Competition Sept. 2019 - Oct. 2019 Cooperate with a team, we are trying to increase the F1 score on differentiating fraud transaction. By writing some functions and applied them to the data, I have found that under certain circumstances, the fraud rate will triple. Combining added variables and machine learning algorithms for binary target variables, we increase the F1 score by 8%. Wine Price Prediction July 2019 - July 2019

Interested in which factors will have stronger impacts on the price of a wine bottle, I applied statistic inferencing and obtained some interesting facts such as wine produced in Canada is among one of the most expensive compared to other countries. After data wrangling, inferencing, the regression models obtain a 46% R^2 score on predicting the price of wine. EDUCATION

University of Liverpool Sept. 2010 - July 2016

BSc Mathematics & Finance 2016

Python, SQL, Data Visualization, Data Wrangling, Statistics Inference, Data Scraping, Finance, Business Analytics, Consulting, Machine Learning Algorithms(Linear/Logistic Regression, Random Forest, Boostings, Classifiers) SKILLS