Nicole Donnelly
Business Analyst II - Counterfeit Crimes Unit at Amazon
Washington, District of Columbia, United States
Summary
👤
Senior🎓
Top SchoolNicole Donnelly is a data-driven technology consultant and analyst with 11 years of experience applying computer forensics, large-scale data collection, analytics, and machine learning to complex investigations and litigation support. Currently a Business Analyst II on Amazon’s Counterfeit Crimes Unit, she blends hands-on Python and SQL expertise with visualization tools like Tableau and QuickSight to turn messy data into actionable insights. Her background includes directing digital forensics at consulting firms, advising capstone projects, and teaching data science as faculty at District Data Labs and Georgetown, where she developed and led technical workshops. Nicole’s career spans both government IT data management and private-sector e-discovery, giving her a rare cross-sector fluency in evidence-grade data handling and operational analytics. Colleagues rely on her knack for web scraping and data wrangling to uncover patterns that others miss, and she often translates technical complexity into clear, teachable outcomes. Based in Washington, DC, she pairs investigatory rigor with an educator’s drive to make analytical methods accessible and repeatable.
11 years of coding experience
11 years of employment as a software developer
Professional Certificate, Professional Certificate at Georgetown University School of Continuing StudiesBA, BA at Rutgers UniversityOther- Exchange Student, Other- Exchange Student at University of Readingnon-degree seeking student, non-degree seeking student at University of Maryland University CollegeGeneral Assembly
Github Skills (35)
scs8
meta-learning8
scraper7
machine-learning7
science7
python7
journal6
data-science6
certificate5
esri5
visual-analytics5
scikit5
rss5
leaflet4
statistics4
Programming languages (2)
Github contributions (5)
nd1/DC_RestaurantViolationForecasting
Jul 2016 - Sep 2016
Contributions:15 commits, 14 pushes, 1 branch in 1 month
forecastingchicagopythoninspectionfood
nd1/pycon_2017
May 2017 - May 2017
Fantastic Data and Where To Find Them: An introduction to APIs, RSS, and Scraping
Contributions:18 commits, 1 push in 10 days
rsspythonscrapingfantasticscraper
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