Requirements - 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 Basic Qualifications: - Master's degree, PhD preferred in Statistics, Mathematics, or a related quantitative field, with 5-8+ years of applied data science experience - Mastery of Python or R, statistical tools such as Stata, SAS and strong SQL - Expertise with ML algorithms (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 Preferred - Experience with Spark/Databricks.