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Data Scientist, Statistician, R, SAS, Python, SQL

Location:
Washington, DC
Salary:
85000
Posted:
May 13, 2018

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Resume:

Nathan E. Fogal

**** * ****** **

Washington, DC 20007

***********@*****.*** 585-***-****

EDUCATION

University of Virginia, Data Science Institute, Charlottesville, VA May 2017 Master of Science in Data Science, GPA: 3.9

Relevant courses: Data Ethics, Data Mining, Data Visualization, GIS, Machine Learning, Statistical Consulting University of Virginia, College of Arts & Sciences, Charlottesville, VA May 2016 Bachelor of Arts in Statistics (Actuarial Finance Concentration), Three-Year Graduate Relevant courses: Linear Models, Machine Learning, Nonparametric Statistics, Sample Surveys, Time Series WORK EXPERIENCE

Accenture, Washington, DC July 2017 – Present

Analytics and Technology Analyst

• Facilitate data-driven decision making and risk management for a federal client through delivery of analytical insight

• Utilize machine learning and statistical modeling to develop proactive fraud models using Python, R, and SAS

• Analyze millions of unstructured transactions using text analytics and data mining for major fraud investigations

• Lead data quality improvement initiatives and strengthen agency budget optimization using time series forecasting

• Drive increased efficiency by automating client-facing reports and producing interactive Tableau data visualizations

• Build enhanced databases in SAP HANA to expand the analytical capabilities of various agency organizations

• Develop and monitor real-time interactive business intelligence dashboards for international clients

• Provide back-end software improvement and code migration support for logistics management systems Critical Incident Analysis Group, Charlottesville, VA August 2013 – May 2017 Program Coordinator Intern

• Led a student team that delivered analytical support to an agency seeking strengthened intergovernmental cooperation

• Communicated complex statistical findings to aid lawyers and doctors in significant court cases

• Built and analyzed datasets of sensitive records using R to reinforce litigation responses for the Virginia DOC

• Orchestrated multiple 50-participant conferences on topics of interest among international law enforcement agencies

• Managed a $50,000 budget and reported to executives regarding financial stability and growth of the organization General Faculty Council, University of Virginia, Charlottesville, VA September 2015 – May 2017 Data Modeling Intern

• Cleaned and analyzed sensitive demographic data using R to increase transparency of faculty government structure

• Utilized Tableau to create visualizations of critical statistical findings for use in board meetings

• Presented recommendations to promote increased diversity among faculty leadership to university officials SELECTED PROJECTS

Adversarial Learning in Credit Card Fraud Detection (Capstone) August 2016 – May 2017

• Collaborated with a major financial institution to develop a novel approach to credit card fraud detection

• Produced defensive and offensive models to clean and analyze 80 million real transactions using Python, R, and AWS

• Constructed adaptive algorithms to instantaneously detect fraudulent transactions prior to approval

• Forecasted evolving fraudulent strategies using game theory to preemptively reinforce the detection models

• Published a technical research paper that won the Best Paper Award at the IEEE SEIDS Conference 2017 Optimizing Uber May 2017

• Developed algorithms using Linear Regression and Gradient Boosted Trees to optimize Uber prices against competitors Understanding Police Shootings February 2017

• Used Random Forests, Association Rule Mining, and BBN’s to determine the leading causes of police shootings globally Sentiment Analysis of the 2016 Presidential Election October 2016

• Applied sentiment analysis to scrapped tweets from Twitter to develop accurate election polls and favorability ratings SKILLS

Technical: Business Intelligence, Data Mining, Data Visualization, Machine Learning, Statistical Modeling, Time Series Programming: Python, R, SAS, SQL, Tableau, Java, ArcGIS, AWS, HTML, JavaScript, SAP HANA Certifications: ICAgile Certified Professional



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