Data Scientist I- Public Health

Cherokee Federal•Atlanta, GA

About The Position

The Bioinformatics Support I – Data Science & Informatics role provides analytical and technical support for public health surveillance, data engineering, and advanced analytics initiatives within CDC’s Division of Global Migration Health (DGMH). This role focuses on building and maintaining data pipelines, performing large-scale data analysis, and supporting the development of statistical models and dashboards that inform operational decision-making. The ideal candidate is comfortable working with complex datasets, developing reproducible workflows, and translating data into actionable insights in a fast-paced public health environment.

Requirements

Master’s degree in Data Science, Bioinformatics, Statistics, Computer Science, Epidemiology, or related quantitative field
Strong experience working with large datasets and complex data structures
Proficiency in Python (preferred), R, or similar programming languages
Proficiency in SQL and database querying
Proficiency in data processing frameworks (e.g., PySpark)
Experience building and maintaining data pipelines and reproducible workflows
Knowledge of statistical modeling, machine learning, or advanced analytics techniques
Strong problem-solving and analytical skills
Ability to manage multiple priorities and deadlines in a fast-paced environment
Strong written and verbal communication skills
Advanced proficiency in Microsoft Office (Outlook, Word, Excel, PowerPoint)
Must pass the pre-employment qualifications of Cherokee Federal
Must be a U.S. citizen or legal permanent resident and provide documentation
An active NACI clearance or the ability to obtain a NACI clearance is required

Nice To Haves

Experience with public health surveillance systems or datasets
Experience with platforms such as Palantir Foundry or CDC 1CDP
Experience developing dashboards or data visualization tools (Tableau, Power BI, or similar)
Familiarity with data governance, security, and compliance in federal environments
Experience integrating data from multiple sources and partners
Exposure to time-series analysis, forecasting, or anomaly detection

Responsibilities

Design, build, and maintain data pipelines to ingest, transform, and validate large datasets supporting public health surveillance efforts
Analyze complex datasets to identify trends, anomalies, and actionable insights that inform program operations and decision-making
Develop and support statistical analyses, basic modeling, and data-driven reporting to support monitoring and forecasting activities
Clean, standardize, and validate data to ensure accuracy, consistency, and usability across systems and reporting outputs
Create dashboards, visualizations, and reports to communicate findings to both technical and non-technical stakeholders
Document data processes, workflows, and standard operating procedures to support reproducibility and data governance
Integrate data from multiple internal systems and external partners, ensuring alignment with program needs
Automate routine data processing and reporting tasks to improve efficiency and reduce manual effort
Collaborate with cross-functional teams, including epidemiologists, bioinformaticians, and program staff to support analytics and data initiatives
Participate in meetings, briefings, and stakeholder engagements to support program coordination and data interpretation