Job Description

Metas Solutions excels in providing strategic consulting, program management, and data-driven analytics to federal public health agencies. Our expertise enhances health systems and delivers measurable outcomes, helping agencies achieve their mission. We collaborate with federal partners to implement agile solutions for national public health initiatives, driving impactful changes through cutting-edge programs that strengthen communities and promote well-being. See www.metassolutions.com for further details about us and careers with Metas.

Job Description:

Metas Solutions is seeking an experienced Public Health Data Scientist to support our client. The Public Health Data Scientist will provide scientific, epidemiologic, statistical, and advanced analytic support.

In this role, you will work with scientists and program staff to define study questions, develop analytic approaches, conduct advanced analyses using large and complex healthcare datasets, and translate findings into actionable public health insights. You will serve as a subject matter expert on the Data Hub data assets, applied technical methodology, computational platforms and cloud-based environment - including Databricks, Posit Workbench and Palantir Foundry – used for completing analyses.

The Public Health Data Scientist will also contribute to emerging analytic activities, including identifying, developing and validating research designs and methodologies which can enhance, and benefit research initiatives facilitated through the CDC Data Hub. This work will incorporate fields including Machine Learning, causal inference and other statistical methods and will focus on improving accessibility of advanced analytics for use in epidemiologic/public health research. The position requires a combination of public health expertise, a strong quantitative skillset, and the ability to independently lead complex analytic activities from study design through analysis, validation, interpretation, and dissemination.

Responsibilities:

• Provide scientific, epidemiologic, statistical, and data analytic support.
• Serve as a subject matter expert for CDC Data Hub datasets, advising scientists and program staff on data structure, limitations, appropriate analytic methods, and interpretations.
• Work independently under guidance to develop research questions, study designs, analytic plans, and methodological approaches supporting public health surveillance, research, response, and other priority activities.
• Conduct advanced analyses of large, complex healthcare and public health datasets, including electronic health records, administrative claims, laboratory, pharmacy, hospital, and other healthcare data.
• Lead development of analytic reports, methodological documentation, technical presentations, publication manuscripts and other scientific products.
• Collaborate with data scientists, epidemiologists, data managers, and engineers to ensure advanced analytics and AI/ML approaches appropriately account for data quality, transformations, lineage, dependencies, and platform capabilities.
• Support exploratory and applied AI/ML analyses, including data preparation, feature engineering, model development, testing, validation, performance evaluation, and interpretation.
• Conduct literature reviews and applied research to inform study designs, analytic methods, and interpretation of findings.
• Conduct analyses and develop reusable analytic workflows within cloud-based and enterprise platforms, including Palantir Foundry, Databricks, and other approved analytic environments.
• Develop, maintain, and review analytic code using Python, R, SQL.
• Review analyses, analytic code, methods, and supporting documentation for methodological rigor, scientific validity, reproducibility, and quality.
• Collaborate with data management and engineering teams to understand data transformations, data quality considerations, and dependencies affecting scientific analyses.
• Promote reusable and reproducible analytic practices through documented code, quality-control procedures, shared repositories, and knowledge transfer.

Qualifications:

• Graduate degree in data science, epidemiology, biostatistics, public health or other quantitative fields with 5+ years of related experience.
• Experience developing and implementing study designs, analytic plans, and methodological approaches supporting public health surveillance, research, response, and other priority activities.
• Experience collaborating with epidemiologists, data scientists, data managers, and engineers to address activities affecting scientific and advanced analytic activities.
• Demonstrated experience analyzing large, complex healthcare or public health datasets, including EHR, administrative claims, laboratory, pharmacy, hospital, survey, or surveillance data.
• Experience with machine learning/AI and advanced statistical modeling, including method development, implementation validation, and interpretation.
• Experience developing, maintaining, and reviewing analytic code and reproducible workflows using Python, R, SQL and other approved tools, including data preparation, quality control, validation, and documentation.
• Has developed and disseminated analytic reports, methodological documentation, technical briefs, presentations, white papers, and scientific publications.
• Experience with Git/GitHub or other version-controlled repositories and reproducible analytic workflows.
• Familiarity with healthcare coding and terminology systems used in healthcare
• Ability to obtain and maintain the required Federal Public Trust clearance.

Preferred Qualifications:

• Experience supporting HHS, CDC, or another Federal public health organization.
• Hands-on experience with Palantir Foundry, including data exploration, transformation, analytics, reusable workflows, and/or analytic product development.
• Experience with Databricks, Microsoft Azure, Posit Workbench, Truveta Studio, or similar cloud-based analytic platforms.
• Experience with advanced methods such as causal inference, Bayesian methods, machine learning, data mining, feature engineering, or natural language processing.
• Experience developing, testing, validating, and evaluating ML/AI models or emerging analytic methods using large healthcare or public health datasets.
• Experience serving as a dataset or data-asset SME, advising users on data structure, limitations, fitness for use, and appropriate interpretation.

Security Requirements:

• Must be US Citizen OR with the ability to obtain a US Government security clearance (Public Trust 5) within a reasonable period.
• Market competitive salary, commensurate with experience and education.
• Comprehensive benefits package available, Medical, Dental, Vision and Life Insurance, Paid Time Off (PTO), 401K with company match, growth, and promotion opportunities.

We are an Equal Opportunity Employer/Veterans/Disabled