Yishan Zhang

Address:**** * **** **, *** ***, Arlington, VA, 22201 Phone:979-***-**** Email:

ac4jda@r.postjobfree.com

Summary

Accomplished Data Analyst skilled in achieving data analysis, modeling structure, and programming optimization. Production process improvement, risk prediction, and establishment of modeling of data expert. Apply data to actual industrial production or business process to estimate risk and possible results, and reduce costs by establishing models, finding issues and, optimization of programmings. Highlights

Experience

Data Analyst, Inbox-America

12/2017--present

• Build User-based and Item-based Recommender System for furniture markets on Python and SQL by using collaborative filtering and SVM(support vector machine)

• Evaluate predicting modeling to improve accuracy

• Establish plans of how to increase sales amount of furniture markets Research Assistant in Peking University, Beijing, China 05/2017-07/2017

• Establish predicting models of Beijing Urban Big Data to visualize city transportation

• Develop a Beijing Urban structural model to predict future development of distribution of population in Beijing.

• Optimize the previous models concerning branching cars in rush hours in Beijing sponsored by DiDi Dache, Inc..

• Using Bayesian models to solve the problems pertinent to “how to improve effectiveness of DiDi taxi of picking up customers at the location considering bad weather interference with cell phone signals

• Excellent Python programming (4+ yrs) • Good research ability(4 + yrs)

• Good operation of Linux Shell (4 + yrs) • Good Knowledge of SPSS(4 + yrs)

• Excellent SAS programming(3 +yrs) • Excellent R programming(3 + yrs)

• Skillful SQL(3 + yrs) • Data modeling and estimation(3+ yrs)

• Web Scraping (HTML,CSS,XPATH)(2+ yrs) • AWS Cloud Computing(2+ yrs)

• Neo4j (2+ yrs)

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• Hadoop (3+ yrs)

• Microsoft Office(6+ yrs) • Statistical Modeling(4+ yrs) Internship in China National Marine Environmental Forecasting Center (NMEFC), Beijing,China

07/2017-08/2018

• Analyze Marine Big Data to model changes in oceanic environment within the recent 10 years to predict the future possibilities to reduce risk of sailing and marine freight.

• Develop the visualization of tracing marine energy permeation and possible environmental pollution caused by energy extraction in oceans on SQL.

• Analysis on future business of marine energy sales and exploitation to improve accuracy of prediction of marine weather.

• Plans on improving the effectiveness of marine energy extraction by using Artesian Neural Network on Python Programming.

Project of Energy Efficiency in North America, Washington, DC, America. 03/2017-05/2017

• Analysis on improving effectiveness of energy extraction and exploitation.

• Use Big Data modeling by R program and SQL to visualize the energy usage and predict the trend of development of energy of electricity and traditional fossil energy.

• Conclusion of most important factors affecting energy efficiency and environmental pollution, and the optimizing point of energy extraction, including location, pressure, temperature and so on.

Internship in Bureau of Geophysical Prospecting INC.,China National Petroleum Corporation.

06/2016-08/2014

• Develop visualization of natural resources exploration by using Landmark and Discovery software.

• Anticipation in project concerning seismic wave analysis and prediction in possible drilling spots for petroleum by SAS

• Improve the programming on optimization of energy efficiency. Education

Bachelor of Science, Geology, 2011–2015

Texas A&M University, College Station, Texas

Major: Geology. GPA:3.2/4.0

Minor: Mathematics. GPA:4.0/4.0

Member Acceptance of Mensa International Organization, 2016 Master of Science, Mathematics and Statistics, 2016 2017 Georgetown University, Washington, DC

Major: Mathematics and Statistics

GPA: 3.90/4.00

Finished courses:

1.Probability Theory/ Application

2.Deterministic Math Models

3.Mathematical/Statistical Computing

4.Mathematical Statistics

5.Numerical Methods

6.Intro to Statistical Learning

7.Advanced Math & Stat Computing

8.Stochastic Simulation

9.Time Series

10.Data Mining

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