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Sunnyvale, California, United States
April 06, 2018

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Jiaman Li

**** ******** **, *********, ** ***** 715-***-****


Rutgers University-Newark, Newark, NJ

Master of Public Administration, Aug. 2016-May.2018

GPA: 3.958/4.0

Honors: SPAA Graduate Commitment to Service Scholarship

Activities: Teaching and Research Assistant at School of Public Affairs and Administration

Related Coursework: Public Policy Process, Applied Statistics, Applied Research Design

Minzu University of China (MUC), Beijing, China

B.A. in Public Administration, June 2016

GPA: 3.85/4.50

Honors: Professional Second-class Scholarship

Activities: Student Committee in School of Management, Minister

On-Campus No. 27 Magazine E-journal, Marketing Officer

University of Wisconsin-Stout, Menomonie, WI

Non-degree Exchange Program, Aug. 2015- May. 2016

GPA: 4.0/4.0

Honors: International Student Scholarship

Chancellor’s Award for Outstanding Academic Achievement


Public Technology Institute, Washington, DC

Summer Research Intern, June 2017- July 2017

- Assisted by the Certified Government Digital Services Professional Certification Program

- Responsible for using online services, periodicals, publications, and other tools to do some research related to the area of digital services delivery

Rutgers University-Newark, Newark, NJ

Teaching Assistant for Economics, February 2017- May 2017, January 2018-Present

- Responsible for helping with grading, inputting and tracking grades

- Responsible for collecting and organizing assignment

- Held office hours to discuss problems students are having in class

Mazars Consulting (Shanghai) Co., Ltd, Beijing Branch, China

Administration Intern, June 2016- August 2016

- Assisted colleagues to receive phone calls and took notes

- Maintenance of HR system, and invited candidates to interview via phone calls

- Assisted in company activities, e.g. annual dinner, company travel, Happy Friday etc.


Credit Card Fraud Detection

- Identified fraud transactions with over 98% accuracy on hugely imbalanced (0.17%) transaction level data, using Synthetic Minority Over-Sampling Technique (SMOTE)

- Implemented machine learning approach including Logistic Regression and Random Forest

- Made Recommendations on designing an automatic fraud detection system with the build models

LANGUAGES Fluent in written and spoken Mandarin and English

Skills Programming language (R, Python, SQL, Stata)

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