Machine Learning Engineer / Data Scientist

Prometheus Federal Services (PFS); Virginia (MN); On-site; USD 90,000 - 120,000; Full time

Job summary

A federal health technology partner is looking for a Machine Learning Engineer/Data Scientist to innovate health analytics for the Department of Veterans Affairs. The candidate will develop advanced machine learning models, collaborate with interdisciplinary teams, and handle large healthcare datasets. A Master's degree and five years of experience in ML/AI are required, along with proficiency in Python and relevant ML libraries. This is a full-time, mid-senior level position based in Virginia, Minnesota.

Qualifications

• Master's degree and five years of relevant experience required.
• Hands-on experience applying ML techniques to real-world problems.
• Fluency in English is mandatory.

Responsibilities

• Develop and deploy cutting-edge data science solutions.
• Collaborate with teams to optimize business operations.
• Perform advanced statistical analyses on large datasets.
• Deploy AI/ML models for decision support systems.
• Continuously research state-of-the-art AI/ML methods.

Skills

Machine Learning

Python

Statistical Modelling

Data Visualization

Education

Master's degree in Data Science or related field

Tools

scikit-learn

TensorFlow

PyTorch

AWS

Azure

GCP

Job description

Overview

Prometheus Federal Services (PFS) is a trusted partner of federal health agencies, seeking a Machine Learning Engineer/Data Scientist to support advanced analytics initiatives within the Department of Veterans Affairs. This position will drive innovation in predictive analytics, machine learning (ML), and artificial intelligence (AI) to improve operational decision-making and health outcomes across the Veterans Health Administration. Additionally, this position will support PFS in scaling tools and expanding knowledge of AI within corporate applications.

Responsibilities

• Drive the development and deployment of cutting-edge data science solutions to address complex organizational challenges
• Collaborate with multi-disciplinary teams, shaping strategic initiatives that innovate and optimize business operations through advanced analytics, predictive modeling, and automation
• Perform advanced statistical analyses and data modeling to extract actionable insights from large, complex federal healthcare datasets
• Design, develop, and deploy AI/ML models for predictive analytics, natural language processing, and decision support systems
• Design, develop, and deploy robust machine learning and deep learning models for a variety of data-driven use cases
• Develop reproducible workflows, documentation, and scalable pipelines for data ingestion, feature engineering, model training, validation, and deployment
• Continuously research and apply state-of-the-art AI/ML methods to improve accuracy, interpretability, and scalability of deployed models
• Drive knowledge sharing by introducing new tools, frameworks, and methodologies reflective of AI/ML best practices
• Support client stakeholders by presenting findings in clear, compelling visualizations and narratives for executive audiences

Minimum Qualifications

• Master's degree in Data Science, Computer Science, Statistics, Applied Mathematics, or a related field
• Minimum five (5) years of experience applying machine learning or AI techniques to solve real-world problems, with a focus on deploying production-grade solutions
• Demonstrated expertise with Python (preferred) or R, including building and packaging reusable code, modules, and libraries
• Hands-on experience with ML libraries such as scikit-learn, TensorFlow, or PyTorch, and a strong understanding of model lifecycle management (training, tuning, deployment, monitoring)
• Demonstrated experience implementing production-grade machine learning solutions and deploying at scale (on-premise or on cloud platforms such as AWS, Azure, or GCP)
• Experience implementing end-to-end Python projects and tooling, including automation scripts, data pipelines, and reproducible workflows
• Proven ability to design, develop, and document RESTful APIs and integrate with major APIs (e.g., OpenAI, Azure Cognitive Services, Hugging Face)
• Familiarity with version control (Git/GitHub), CI/CD pipelines, and DevOps/MLOps best practices
• Strong understanding of statistical modeling, supervised/unsupervised learning, and model evaluation metrics
• Must have strong typing and computer skills
• Must be able to read, understand, speak, and write English fluently
• Authorized to work in the U.S. indefinitely without sponsorship
• Ability to obtain a public trust

Preferred Qualifications

• Ten (10) years of experience applying machine learning and AI techniques to solve real-world problems
• Experience supporting the Department of Veterans Affairs or other federal health systems
• Familiarity with VHA data sources (CDW, VSSC, IPEC) and healthcare-related metrics
• Knowledge of MLOps best practices, including CI/CD for ML pipelines and modeling monitoring
• Experience communicating technical results to senior government leaders and non-technical stakeholders

Seniority level

Mid-Senior level

Employment type

Full-time

Job function

Sales, General Business, and Education

Industries

Wireless Services, Telecommunications, and Communications Equipment Manufacturing