Partner with stakeholders to scope questions and assumptions, support solution design, and facilitate project execution
Design and implement robust data ingestion, storage, integration, processing, retrieval, and management strategies for research datasets
Build transparent, reproducible pipelines and analysis environments in cloud infrastructures
Produce crisp exhibits and memos that explain methods, limitations, and uncertainty
Facilitate and execute data-driven research by applying sophisticated statistical, machine learning, and computational methods to analyze complex datasets related to computer and information science
Create compelling data visualizations and reports that convey complex research findings in a clear and accessible manner to both technical and non-technical stakeholders
Support defensible analytics and econometric/causal inference workstreams, translating ambiguous business or legal questions into testable hypotheses and clear, client-ready findings
Design and execute rigorous studies (e.g., difference-in-differences, panel models with fixed/random effects, instrumental variables/2SLS, time series/forecasting, etc.) to turn multi-source datasets into documented, auditable results
Mentor teammates on best practices
Stay updated on the latest academic research and industry advancements in data science, AI, and information systems, and apply relevant findings to ongoing projects

Bachelors degree with 8+ years of applied data science experience or a Master’s degree with 6+ years of prior relevant experience
Mastery of Python or R, statistical tools such as Stata, SAS and strong SQL
Expertise with ML algorithms (e.g. model selection, evaluation, feature engineering, etc.)
Expertise with application of AI to deliver insights with optimal performance, cost savings, etc. using structured, unstructured data
Expertise with data visualization tools (e.g. Tableau, Matplotlib)
Experience processing large datasets, deploying LLMs in government cloud data platforms (e.g. Azure ADLS/Databricks/Azure ML, or equivalents)
Comparative understanding of LLMs (e.g. Claude Code, ChatGPT), and tradeoffs in terms of capabilities, cost, and performance
Excellent problem-solving skills and the ability to think critically and analytically to address complex research challenges
Exceptional verbal and written communication skills and a bias toward rigor, clarity, and defensibility over black-box modeling are essential
Familiarity with FISMA/NIST/Zero Trust security frameworks
Current Principal Data Scientist (PDS) Certification
U.S Citizenship required.

Senior Data Scientist

Key skills