Senior Data Scientist

Position Summary
Prometheus Federal Services (PFS) is a trusted partner of federal health agencies. We are seeking a Senior Data Scientist to support Department of Veterans Affairs (VA) programs through advanced analytics, predictive modeling, data science, and AI-enabled solutions. This role will focus on transforming complex VA data assets into actionable insights that support operational decision-making, healthcare outcomes, data modernization initiatives, and enterprise reporting.

The Senior Data Scientist will collaborate with business stakeholders, data engineers, analysts, and program leadership to design, develop, and operationalize advanced analytical solutions. The ideal candidate brings deep expertise in statistical analysis, machine learning, data engineering concepts, and healthcare analytics, along with experience working within complex federal data environments.

Reasonable Accommodations Statement
To succeed in this job, an individual must be able to satisfactorily perform each essential duty. Reasonable Accommodations may be made to enable qualified individuals with disabilities to perform essential functions.

Essential Duties and Responsibilities
Data Science, Advanced Analytics & AI/ML
- Develop and implement advanced analytical models to identify trends, patterns, risks, and opportunities within large and complex datasets.

- Design, build, and deploy machine learning models to support predictive and prescriptive decision-making.

- Apply statistical techniques and data science methodologies to solve complex business and operational challenges.

- Develop forecasting, classification, clustering, anomaly detection, and optimization models to support program objectives.

- Support AI-enabled analytical solutions that improve operational insight, performance measurement, and resource planning.

- Evaluate emerging AI, machine learning, and advanced analytics technologies for applicability within VA environments.

- Develop model monitoring and evaluation frameworks to ensure accuracy, stability, explainability, and performance.

Data Exploration, Preparation & Feature Engineering
- Conduct exploratory data analysis (EDA) to uncover patterns, anomalies, and key business drivers.

- Perform data profiling and quality assessments to identify issues impacting analytical outcomes.

- Develop feature engineering strategies to improve model performance and business relevance.

- Prepare and transform structured and semi-structured datasets for advanced analytical applications.

- Collaborate with data engineering teams to establish scalable analytical datasets and model-ready data pipelines.

Data Integration, Engineering & Architecture Collaboration
- Partner with data engineers and architects to integrate data across diverse VA systems, databases, APIs, and enterprise platforms.

- Support the design and optimization of data pipelines and analytical workflows.

- Contribute to data modeling efforts that improve accessibility, scalability, and performance of analytical solutions.

- Assist in developing reusable analytical frameworks and data science assets across programs.

- Ensure analytical solutions align with data governance, security, and compliance requirements.

Business Partnership, Strategy & Communication
- Translate business questions, policy objectives, and operational needs into analytical approaches and measurable outcomes.

- Present analytical findings, model outputs, and recommendations to technical and non-technical stakeholders.

- Develop executive-level briefings, data visualizations, and decision-support materials.

- Partner with program leadership to identify opportunities to transition from descriptive reporting to predictive and prescriptive analytics.

- Communicate model assumptions, limitations, and risks to stakeholders in a clear and understandable manner.

Governance, Documentation & Continuous Improvement
- Develop and maintain documentation for analytical methods,