Data Scientist

CDC Foundation

5h•$92,700 - $134,275•Remote

About The Position

The Data Scientist will play a crucial role in advancing the CDC Foundation's mission by leveraging data to inform strategic decisions and initiatives in a public health organization. This role is aligned to the Workforce Acceleration Initiative (WAI). WAI is a federally funded CDC Foundation program with the goal of helping the nation’s public health agencies by providing them with the technology and data experts they need to accelerate their information system improvements. Working within Illinois Department of Public Health , the Data Scientist will develop public health measures and apply statistical, machine learning, and AI methods to analyze complex datasets and build predictive models, while collaborating closely with epidemiologists, stakeholders, and data visualization specialists to deliver clear, actionable insights in compliance with privacy and data governance standards. The Data Scientist will be hired by the CDC Foundation and assigned to the Illinois Department of Public Health informatics team. This position is eligible for a fully remote work arrangement for U.S. based candidates.

Requirements

Bachelor’s degree or higher in Data Science, Statistics, Epidemiology, Informatics or related fields. Master’s or PhD in related field preferred.
Minimum 3-5 years of relevant professional experience developing analytical models, including regression, classification, or predictive modeling
Demonstrated experience applying statistical analysis and data science techniques to large, complex datasets.
Proficiency in programming languages such as Python or R.
Experience with data manipulation and analysis tools (SQL, Python, and Snowflake is preferred).
Knowledge of machine learning frameworks (e.g., TensorFlow, Scikit-learn).
Knowledge of implementing AI tools to interact with datasets.
Strong analytical thinking and problem-solving abilities.
Ability to interpret complex datasets and derive meaningful insights.
Excellent verbal and written communication skills.
Ability to convey technical concepts to non-technical partners effectively.
Flexibility to adapt to evolving project requirements and priorities.
Outstanding interpersonal and teamwork skills; collegial; energetic; and able to develop productive relationships with colleagues, partners, and partners.
Demonstrated ability to work well independently and within teams
Experience working in a virtual environment with remote partners and teams
Proficiency in Microsoft Office.

Nice To Haves

Master’s or PhD in related field preferred.
Professional certifications in data science, machine learning, or public health analytics preferred.

Responsibilities

Analyze complex, multi-source public health datasets to identify trends, patterns, disparities, and emerging risks.
Design, develop, and maintain statistical, machine-learning, and AI-based models to support disease surveillance, population health measurement, and predictive analytics.
Build and validate predictive models to anticipate disease patterns, assess risk factors, and inform prevention and intervention strategies.
Continuously evaluate and optimize analytic methods and algorithms to improve model accuracy, performance, and interpretability.
Translate complex analytical results into clear, actionable insights, including explaining model logic, assumptions, limitations, and appropriate use.
Work closely with epidemiologists, program staff, leadership, and external subject-matter experts to ensure analyses align with public health context, policy needs, and operational realities.
Partner with data visualization specialists to develop clear, accurate, and decision-ready dashboards and analytic products.
Ensure analytic approaches comply with privacy laws, data governance policies, and organizational suppression and disclosure-avoidance standards.
Support development of standardized measures, indicators, and metrics used across programs and external reporting.
Provide analytic guidance to inform public health policy, program planning, and evaluation.
Stay current on emerging data science, AI/ML, and public health analytics methods, and pilot innovative approaches to address complex health challenges.
Up to 10% domestic travel may be required.