Data Scientist/Data Science Lead

Role Overview

The Data Scientist / Data Science Lead will provide hands-on analytical leadership across Department of Veterans Affairs (VA) modernization initiatives. The role combines advanced analytics, statistical and machine-learning methods, data-quality rigor, analytical coding, technical review, and decision support for complex mission and operational questions.

What You Will Do

The Data Scientist / Data Science Lead will lead analytical strategy for complex operational, clinical, workflow, and technology questions, assess data readiness, quality, sensitivity, lineage, authoritative sources, and fitness for intended measures, and develop and review statistical models, machine-learning methods, exploratory analyses, and AI/LLM evaluations.

Why It Might Be a Fit

The ideal candidate combines strong statistical coding with practical data-quality rigor and can explain evidence, uncertainty, bias, missingness, and limitations to technical, operational, clinical, and executive audiences.

Requirements

• Bachelor’s degree in data science, statistics, mathematics, computer science, operations research, economics, engineering, public health, or a related quantitative field.
• 7+ years in data science, advanced analytics, machine learning, statistical analysis, or related work.
• Strong hands-on Python and SQL skills with demonstrated statistical modeling, validation, and complex-data interpretation experience.
• Experience translating ambiguous business, operational, or clinical questions into defensible analytical methods and decision products.
• Recommended certification: cloud data science/ML, analytics, or data-platform credential from Microsoft/Azure, AWS, Google Cloud, Databricks, or comparable provider.
• Ability to satisfy VA personnel vetting and requirements for sensitive or regulated data.
• Strong statistical foundation covering regression, classification, sampling, validation, uncertainty, experimental or quasi-experimental reasoning, and appropriate interpretation of observational data.
• Demonstrated ability to work with large, messy, multi-source datasets and independently diagnose data-quality, missingness, leakage, representativeness, and lineage concerns before modeling.
• Technical leadership experience reviewing others’ analytical work, mentoring staff, setting coding and validation standards, and explaining complex findings to senior non-technical stakeholders.
• Experience owning analytical work from problem formulation through data acquisition, modeling, validation, interpretation, executive communication, and transition to recurring or operational use.
• Strong written and verbal communication skills for explaining statistical concepts, uncertainty, model behavior, and data limitations without either oversimplifying or overwhelming the audience.

Benefits

• Target salary range: $110,000-$145,000
• Health insurance
• Vision insurance
• Dental insurance
• 401(k) or pension plan
• Paid time off
• Paid holidays
• Flexible work arrangements