Prometheus Federal Services
Machine Learning Engineer / Data Scientist
Prometheus Federal Services, Salem, Virginia, us, 24155
Position Summary
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.
Essential Duties and 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 Qualification
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 Qualification
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.
All qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.
This position may be subject to client or government vaccination, policy, or requirements that may change from time to time.
The work location is flexible if the company approves it, except that the position may not be performed remotely from Colorado.
PFS offers a comprehensive benefits package that includes health insurance, dental and vision insurance, flexible spending accounts, disability insurance, life insurance, a retirement plan, paid time off, remote work, and other benefits to accommodate what matters most to you and your family. Learn more about PFS Benefits.
Note: PFS benefits, compensation, and bonuses are subject to eligibility requirements and other applicable plan or program terms.
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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.
Essential Duties and 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 Qualification
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 Qualification
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.
All qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.
This position may be subject to client or government vaccination, policy, or requirements that may change from time to time.
The work location is flexible if the company approves it, except that the position may not be performed remotely from Colorado.
PFS offers a comprehensive benefits package that includes health insurance, dental and vision insurance, flexible spending accounts, disability insurance, life insurance, a retirement plan, paid time off, remote work, and other benefits to accommodate what matters most to you and your family. Learn more about PFS Benefits.
Note: PFS benefits, compensation, and bonuses are subject to eligibility requirements and other applicable plan or program terms.
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