This job is closed
Applications are no longer available for this announcement. Explore current related opportunities below.
Job description
Position Summary
Prometheus Federal Services (PFS) is a trusted partner of federal health agencies. We are seeking aSenior Data Scientistto 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, 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 Qualification
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 moreabout 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
#J-18808-Ljbffr
Worksite address
fairfax, VA, 22032, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.