Senior Data Scientist – Statistical Modeling, AI/ML

This is a fully remote position, open to applicants in Virginia.

📋 Description

• Lead the development of statistical modeling, AI/ML evaluation, and analytical decision support for the modernization of VA EHR, operational reporting, and executive-level analytics initiatives.

• Design, assess, and articulate statistical and machine learning models, encompassing distributional assumptions, matrix-based techniques, dimension reduction, clustering, natural language processing, simulation, time-series analysis, Bayesian techniques, and model constraints.

• Evaluate model quality, reliability, bias, drift, and operational applicability; recognize when an analytical method is statistically invalid or unsuitable for the given data.

• Act as the point of contact for data governance and quality assurance, proactively spotting defects, gaps, anomalies, reporting inconsistencies, data capture challenges, and root causes within intricate datasets and reporting frameworks.

• Create, sustain, and document reproducible analytics using R, including R packages, scripts, pipelines, dashboards, and governed reporting outputs.

• Integrate and validate data from various sources such as enterprise healthcare systems, operational data, EHR, ServiceNow, Corporate Data Warehouse (CDW), Databricks/Azure, and others to facilitate accurate program reporting.

• Convert stakeholder inquiries into actionable metrics, define KPIs, establish data validation rules, outline dashboard needs, conduct quality checks, and generate recurring reporting products for PMO, functional, and executive audiences.

• Provide guidance on data governance, provenance, metadata management, version control, access policies, code reviews, documentation, and production standards for analytics teams.

• Utilize Git/GitHub and documentation workflows to enhance version control, collaborative development, pull requests, code reviews, reproducibility, and transparent analytical delivery.

• Collaborate with analysts, data engineers, program managers, and VA stakeholders to transition ad hoc analyses into governed, repeatable, auditable data products and reporting processes.

• Contribute to Agile/SAFe delivery by defining features, user stories, acceptance criteria, sprint-ready analytical tasks, and backlog priorities.

⛳️ Requirements

• A minimum of 5 years of practical experience in data science, statistics, machine learning, health informatics, data engineering, or analytics within complex enterprise or healthcare settings; experience with federal health, VA, or VHA is highly desirable.

• An advanced degree or equivalent experience in statistics, biostatistics, mathematics, data science, computer science, public health, health informatics, or a related quantitative discipline.

• A robust theoretical and practical foundation in statistics, covering statistical distributions, mathematical modeling, matrix/linear algebra concepts, inference, uncertainty, and model diagnostics.

• Proven experience in AI/ML, with the ability to assess model appropriateness and reliability, diagnosing situations where models underperform, drift, become biased, or fail.

• Advanced expertise in R for statistical computing, modeling, reproducible analytics, and tool development; experience in developing or maintaining R packages is highly regarded.

• Strong SQL capabilities for querying, joining, validating, and transforming extensive datasets; familiarity with Python is preferred.

• Practical experience using Git and GitHub for version control, collaboration, code review, and reproducible delivery.

• Background in supporting data governance, ensuring data quality, stewardship, metadata management, lineage, provenance, versioning, access control, and documentation in analytics.

• Excellent communication and documentation skills, capable of briefing executives, translating technical insights into operational implications, and guiding teams toward clean, auditable, and compliant analytics.

• U.S. Citizenship and the ability to obtain a Public Trust clearance.

🏝️ Benefits

• Health insurance

• Professional development opportunities

• Flexible work arrangements