Data Scientist at Prometheus Federal Services

Fairfax, Virginia, United States -

Full Time

Start Date

Immediate

Expiry Date

18 Jul, 26

Salary

0.0

Posted On

19 Apr, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data science, Statistics, Machine learning, Artificial intelligence, Databricks, Python, R, SQL, Azure, AWS, Spark, Predictive modeling, Data visualization, Power BI, MLOps, Agile

Industry

Professional Training and Coaching

Description

Position Summary Prometheus Federal Services (PFS) is a trusted partner of federal health agencies. We are exploring the addition of an experienced Data Scientist to support the Department of Veterans Affairs (VA) and federal health programs. The ideal candidate brings strong expertise in statistics, machine learning, and AI, along with hands-on experience using Databricks and cloud‑native analytics tools to develop scalable, high‑impact analytical solutions. This role will support data-driven decision-making across federal health environments by developing predictive models, conducting advanced statistical analysis, and building reproducible analytical workflows. This role will collaborate with data engineers, analysts, clinicians, and program stakeholders to transform complex healthcare data into actionable insights that improve operations, outcomes, and mission performance. Essential Duties and Responsibilities Apply advanced statistical methods (e.g., regression, time-series analysis, survival analysis, mixed models) to federal health datasets. Conduct exploratory data analysis (EDA) to identify trends, anomalies, and actionable insights. Develop, validate, and deploy machine learning and AI models for classification, prediction, clustering, and optimization. Perform feature engineering, model evaluation, and interpretability analysis to ensure transparency and reliability. Document analytical methods, assumptions, and results for technical and non‑technical audiences. Build reproducible ML workflows using Databricks, MLflow, AzureML services, implementing model monitoring, performance tracking, and retraining strategies. Collaborate with engineering teams to orchestrate model deployment, monitoring, and integration. Use Azure or AWS analytics services (e.g., Azure Data Factory, Synapse, AzureML, S3, Glue, SageMaker) to support scalable analytics and ML workloads. Present analytical findings, model outputs, and recommendations to program leadership and stakeholders. Document workflows, code, models, and analytical processes to support transparency and reproducibility. Participate in Agile ceremonies and contribute to continuous improvement across data engineering, data science, and analytics product development. Minimum Qualifications Bachelor’s degree 4+ years of experience in data science, statistical analysis, or machine learning Strong proficiency in statistics, including hypothesis testing, modeling, and experimental design. Hands-on experience with Databricks, Spark, and cloud-native analytics tools (Azure or AWS). Experience in Python, R, and SQL for data manipulation, modeling, and analysis, and Power BI or other visualization tools. Experience developing data and analytics products in federal health environments, including working with clinical, operational, and financial data. Authorized to work in the U.S. indefinitely without sponsorship Ability to obtain a public trust Preferred Qualification Master’s degree in a related field. Experience developing and deploying machine learning models in production or environments. Experience with MLOps practices (CI/CD, model monitoring, versioning). Knowledge of data governance, metadata management, or data quality frameworks. Compensation & Benefits PFS offers a benefits package that may include health, dental, and vision coverage; flexible spending accounts; disability and life insurance; retirement plan; paid time off; and other programs to support employees and their families. Learn more about PFS Benefits. PFS benefits, compensation, and bonuses are determined by various factors, including but not limited to location, the individual's particular combination of education, knowledge, skills, competencies, and experience, as well as contract and organizational requirements. Equal Employment Opportunity All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, parental status, national origin, age, disability, genetic information, political affiliation, military service, or other status protected by law. Accommodations PFS is committed to providing equal employment opportunities to all applicants. If you require a reasonable accommodation during the application or interview process, please contact us at recruiting@pfs.us. Reasonable accommodations are available to ensure applicants with disabilities have equal access to the hiring process, in accordance with the Americans with Disabilities Act (ADA) and applicable laws. Workplace Health, Safety, and Compliance This position may be subject to client‑specific or government‑mandated vaccination, health, or safety requirements, which may change over time. Texting Privacy Policy and Information: Message type: Informational; you will receive text messages regarding your application and potentially regarding interview scheduling. No mobile information will be shared with third parties/affiliates for marketing/promotional purposes. Message frequency will vary depending on the application process. Msg & data rates may apply. Opt out at any time by texting "stop".

Responsibilities

Develop predictive models and conduct advanced statistical analysis to support data-driven decision-making in federal health environments. Collaborate with cross-functional teams to build reproducible analytical workflows and deploy machine learning solutions.