Senior Data Scientist

ONEGLOBE LLC • Washington, DC

5d • Hybrid

About The Position

This role involves conceptualizing research problems, designing studies, and leading the development of advanced analytic and ML solutions. The position requires translating ambiguous mission questions into clearly defined hypotheses, data requirements, and modeling approaches. Responsibilities include authoring and reviewing implementation roadmaps, data exploration reports, model prototype evaluations, and final model analysis reports. The role also involves building, validating, and hardening production models, including model cards, bias and fairness assessments, drift monitoring, and reproducibility artifacts. Additionally, the Senior Data Scientist will lead code reviews, establish coding standards, mentor team members, and continuously update analytic dashboards. The position requires representing the team in technical reviews and stakeholder briefings, advising senior personnel, and staying current on emerging ML, MLOps, and responsible-AI practices.

Requirements

• Ten (10)+ years of relevant experience in applied research, big data analytics, statistics, applied mathematics, data science, computer science, or operations research.
• Seven (7)+ years of direct experience in machine learning.
• Master's or Ph.D. in Statistics, Applied Mathematics, Data Science, Computer Science, Operations Research, or a closely related quantitative or technical discipline. (Ph.D. may substitute for up to three years of experience.)
• Demonstrated ability to create and validate data mining methods, ML models, and analytical results delivered through reporting and visualization.
• Strong communication skills covering analysis techniques, testing, and model validation processes for both technical and non-technical audiences.
• U.S. Citizenship required.
• Candidates must currently possess or be able to favorably pass a five (5) year federal background investigation prior to start.
• All candidates must clear OneGlobe's pre-screening process, which includes review for felony convictions in the past 36 months, illegal drug use in the past 12 months, relevant misconduct, and a financial background check.

Nice To Haves

• Experience in financial crime, fraud detection, regulatory analytics, supply-chain, or other high-stakes mission domains.
• Hands-on experience with modern NLP / LLMs — including retrieval-augmented generation (RAG), embedding models, fine-tuning, prompt engineering, and evaluation frameworks
• Experience with graph analytics for entity resolution, network risk, and link analysis.
• Experience with MLOps pipelines, feature stores, model registries, and production monitoring for drift and bias
• Publications, patents, or open-source contributions in machine learning.

Responsibilities

• Conceptualize research problems, design studies, and lead the development of advanced analytic and ML solutions across supervised, unsupervised, NLP, graph, and (where appropriate) generative-AI techniques.
• Translate ambiguous mission questions into clearly defined hypotheses, data requirements, and modeling approaches.
• Author and review implementation roadmaps, data exploration reports, model prototype evaluations, and final model analysis reports.
• Build, validate, and harden production models — including model cards, bias and fairness assessments, drift monitoring, and reproducibility artifacts.
• Lead code reviews, establish coding standards, and mentor data scientists and analysts on the team.
• Continuously update and enhance analytic dashboards used to model real-world scenarios and identify potential mission impacts.
• Represent the team in technical reviews, working groups, and stakeholder briefings; advise senior project personnel on technical matters.
• Stay current on emerging ML, MLOps, and responsible-AI practices and recommend adoption where they advance the mission.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior