Associate Data Scientist

Summary And Description

Thomson Reuters Special Services (TRSS) is looking for a Data Scientist to support our Federal Law Enforcement customers. TRSS Data Scientists serve several Federal Law Enforcement agencies by collecting, integrating, resolving, analyzing, modeling, and explaining large data in support of complex investigations. Success in this role requires strong technical depth, the initiative to operate with minimal direction, creativity to develop novel solutions, and a mission‑focused mindset.

TRSS Data Scientists support the full range of Federal Law Enforcement missions including, but not limited to:
Emerging Threat Detection, Money Laundering, Fraud, Force Protection, Human Rights Crimes, Transnational Crime, and more. Outside of contract work, TRSS Data Scientists contribute to internal innovation by participating in research and development (R&D), developing and maintaining shared capabilities, strengthening technical skills, and supporting business development efforts such as proof‑of‑concept projects and capabilities briefings.

This opportunity is specifically for positions located on US Government customer sites in the Washington, DC area. This is not a telework position.

TRSS Data Scientist candidates must possess the following minimum qualifications. Please ensure your resume and application clearly demonstrate that you have:

• United States Citizenship (essential to comply with government contract requirements).
• Ability to obtain and maintain a U.S. security clearance or agency work suitability determination, as required by assignment.
• Willingness to work full time, on‑site, embedded at U.S. Government offices in the Washington, DC area. (Specific office assignments are subject to change).
• Bachelor’s or Master’s Degree in a technical field (e.g., data science, statistics, computer science, mathematics, physical/biological sciences, or geographic information systems (GIS), etc.).
• At least 3 years of relevant experience. Relevant experience can include some combination of:
  • Large Data Management: querying, extracting, cleaning, verifying, resolving, and maintaining data.
  • Large Data Analysis: statistical methods, graph networks, anomaly detection, spatial analysis, pattern‑of‑life, sentiment analysis.
  • Large Data Modeling: risk modeling, community detection, classification, computer vision, and general application of machine learning (ML) and artificial intelligence (AI) models.
  • Large Data Storytelling: explaining insights and methodology to a non‑technical audience, dashboards, plots & visualizations, direct experience with customers.
  • Programming:
    Candidates must have practical experience writing, editing, customizing, and executing code written in Python.
  • SQL proficiency:
    Candidates must have experience using SQL for data extraction, pipelining, or exploration.
• Ability to handle sensitive, confidential, or regulated data in accordance with applicable policies and requirements. Ability to interface directly with customers at all levels and be a representative of TRSS.
• Ability to work both independently and as a member of a team. Teams may include other Data Scientists or be cross‑disciplinary and include Subject Matter Expert Analysts and/or Data Engineers.
• Ability to interpret customer requests and/or problem statements into clear project plans, develop project goals and methods, and to deliver actionable results within required time frames.

Preference will be given to candidates who possess the minimum qualifications and the following preferred qualifications. Please ensure your resume and application clearly demonstrate that you have:

• Current/Active government work suitability or security clearance.
• Experience working with law enforcement agencies.
• Programming skills in multiple languages other than Python (Python is a minimum requirement) including R, Java, or SQL.
• Experience with software development, including managing collaborative codebases, version control, linting/testing, containerization, and interacting with REST APIs.

• Hybrid Work Model:
  We’ve adopted a flexible hybrid working environment (2‑3 days a week in the office depending on the…