Current Work Experience
Cohen Milstein Sellers & Toll LLP
Washington, DC
Senior Data Engineer Jan 2026 - Present
Data Engineer Sep 2022 - Dec 2025
- Create and maintain custom ETL library written in Python, speeding up data processing times by 10x and data loading times by 50x.
- Refactor legacy SQL scripts and procedures to leverage newer SQL Server features and follow modern coding standards; the most CPU intensive job now runs in a quarter of the time on a 4-core Azure Managed Instance, down from an 8-core Azure VM, saving over $10,000 per year in compute costs.
- Build and maintain a suite of Azure Function Apps in Python that automate case intelligence workflows, including a daily SEC filing monitor that populates a database of filings used by downstream applications for faster lookup.
- Serve as the technical representative on the Firm's AI Committee alongside senior attorneys and partners; organize AI trainings and submit recommendations on AI tool adoption to the Executive Committee.
Relevant Work Experience
Grant Thornton LLP
Washington, DC
Manager - Statistician Aug 2022
Senior Associate - Statistician May 2021 - July 2022
- Designed dozens of statistical samples across a variety of federal and state tax engagements, including R&D tax credits, depreciation studies, and domestic activity tests, saving hundreds to thousands of staff hours per engagement.
- Helped win over $8 million in government contract awards in 2022 by authoring technical sections related to statistical sampling and data analytics in RFPs.
- As part of the Washington National Tax Office, researched and implemented efficient sampling methodologies and automated internal processes via R and Python scripting; conducted simulation studies to validate sampling efficiency, statistical inference and prediction performance, and confidence coverage.
Cohen Milstein Sellers & Toll, PLLC
Washington, DC
Data Analyst Jun 2016 - May 2019
- Researched securities frauds and market manipulation involving various financial instruments; frequently worked with Antitrust or ERISA practice group attorneys to assist with financial data analysis.
- Analyzed trading data sets, recognized trends and patterns, validated data integrity; audited and monitored investment data for institutional investors to calculate potential damages relating to securities class actions.
- Developed custom data pipelines by integrating Bloomberg API, VBA, SQL, and Python to automate and assist with efficient data analysis, formatting, and validation.