Data Analyst Python

Xinyu Li

adchqg@r.postjobfree.com +1-404-***-****

seeking: business/data analyst or related roles

EDUCATION

Georgia Institute of Technology Atlanta, Georgia

Master of Science in Statistics (double major: Economics) Aug. 2018 – May. 2020

• Cumulative GPA: 3.82/4.0

Zhongnan University of Economics and Law Hubei, China Bachelor of management in Financial Management (major) Sep. 2014 - June 2018 Bachelor of science in Financial Statistics (minor) Mar. 2015 - June 2018

• Cumulative GPA: 85.22/100

SKILLS

• Programming Skills: Python, MySQL, SPSS, R

• Finance: CFA level I

• Others: Tableau, Excel (pivot tables, vlookup, etc.) INTERNSHIPS EXPERIENCE

Citic Securities Shanghai, China

Research Analyst Intern May. 2019 - Aug. 2019

• Established valuation models of target companies by analyzing their business process and helped improve their strategies

• Communicated with clients to collect operating information and articulated technical concepts to non-technical groups

• Independently completed 2 in-depth company research reports of the paper industry, especially focusing on financial performance and development of products, capacity and channel construction

• Collected price data of paper industry using Macros in VBA to update the database weekly and visualized them using Tableau to distribute data insights

China Galaxy Securities Beijing, China

Information Analyst Intern July 2017 - Aug. 2017

• Used Tinysoft Database that required SQL to extract historical data and called functions with basic stock selection index to realize quantitative transactions, including automatic trading, programmatic trading, algorithmic trading, etc.

• Tracked industry trends and company activities and participated in requirement analyses by monitoring data

• Forecast stock list variations of 4 equity indices based on the construction of indices and earnings change PROJECT EXPERIENCE

Non-parametric Data Analysis on Personal Savings Rate from US Economic Time Series Data Using R Nov. 2019 – Dec. 2019

• Went through kernel- and spline-regression fits to Y-data and compared the fitting results using the leave-one-out cross-validation procedure

• Made predictions and constructed the Bias-Corrected Bootstrap confidence intervals using these two regression methods

• Identified and interpreted trends to derive insights and structure the results into a 18-page PowerPoint to deliver final presentation to whole class

Commute Demands Integration Based on the NYC Taxi Trip Data Using Python, D3.js and Tableau Sep. 2019 – Nov. 2019

• Classified commute demands (routes, time, location, etc.) with k-means clustering by cleaning and processing 11.0GB data

• Visualized cluster distributions on the map and analyzed the commute behaviors through Statistical graphics by Tableau

• Helped more than 100 passengers and drivers to choose routes and pick up location A/B Testing to Determine the Improvement of the Website Design Using R and Python July 2019

• Cleaned the mass dataset with more than 7,000 rows and used Python with pandas, numpy to conducted the A/B test

• Utilized the hypothesis test to provide campaign reporting requirements and deliver campaign results

• Improved the conversion rate by around 5.6%

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