Senior Data Scientist

About the role

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.

Essential Functions & 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, models, data sources, assumptions, and validation procedures

Support analytical governance and best practices related to model lifecycle management and reproducibility

Participate in peer reviews and quality assurance activities for analytical products

Continuously evaluate new methodologies and technologies to improve analytical capabilities and program outcomes

Mentor junior data scientists, analysts, and technical team members

Minimum Qualifications

Bachelor's degree in Data Science, Statistics, Computer Science, Applied Mathematics, Operations Research, Engineering, Healthcare Informatics, or a related field

8+ years of experience in data science, advanced analytics, machine learning, or related technical roles

Strong proficiency in Python for data science and machine learning applications (e.g., pandas, NumPy, scikit-learn, TensorFlow, PyTorch, or similar)

Advanced knowledge of statistical methods, predictive modeling, and machine learning techniques

Strong proficiency in SQL for data extraction, transformation, and analysis

Experience developing and validating machine learning models, including classification, regression, clustering, forecasting, and anomaly detection

Experience conducting exploratory data analysis and communicating insights to diverse audiences

Familiarity with model evaluation techniques, performance metrics, and validation methodologies

Experience working with large-scale structured and semi-structured datasets

Understanding of data engineering concepts, including ETL/ELT processes, data pipelines, and cloud-based data platforms

Strong problem-solving, critical thinking, and analytical skills

Excellent written and verbal communication skills

Authorized to work in the U.S. indefinitely without sponsorship

Ability to obtain a Public Trust clearance

Preferred Qualifications

Master's degree or PhD in Data Science, Statistics, Computer Science, Applied Mathematics, Operations Research, Engineering, Healthcare Informatics, or a related discipline

Experience supporting the Department of Veterans Affairs (VA), Veterans Health Administration (VHA), or other federal healthcare agencies

Experience working with healthcare, clinical, claims, operational, or population health datasets

Experience with cloud-based analytics platforms such as Azure Synapse, Azure Machine Learning, Databricks, AWS, or comparable environments

Familiarity with Power BI, Tableau, or other business intelligence and visualization platforms

Experience supporting enterprise data modernization, governance, or digital transformation initiatives

Experience developing explainable AI (XAI) and responsible AI solutions in regulated environments

Experience mentoring and leading technical teams or analytical workstreams

Compensation & Benefits

PFS offers a benefits package that may include health, dental, and vision coverage; flexible spending accounts; disability and life insurance; a retirement plan; paid time off; and other programs to support employees and their families. Learn more about PFS Benefits.

The posted salary range represents PFS's good-faith estimate for this role. Actual compensation offered will be determined by a combination of factors, including but not limited to: the candidate's education, knowledge, skills, competencies, and experience; internal equity; geographic location; and contract and organizational requirements. PFS is committed to fair, consistent, and equitable compensation practices across the organization, and offers are calibrated to maintain internal pay equity while remaining competitive in the external market.

Salary Range: $100,000 - $140,000