Data Scientist

CDC Foundation•Delaware, DE

12d•$45 - $65•Remote

About The Position

The CDC Foundation is seeking a Data Scientist to apply advanced analytics, statistical techniques, and machine learning to support strategic decisions and initiatives in public health. The position works within the Delaware Division of Public Health Epidemiology Section to derive insights for outbreak response, surveillance, and preparedness, including measles, while supporting improvements to data and information systems. The individual will be hired by the CDC Foundation and assigned to the Delaware Division of Public Health Epidemiology Section. This is a remote position for someone based in the United States, scheduled for 20 hours per week, with a position end date of April 30, 2027. The role is part of a dynamic public health program, and responsibilities may be expanded or updated as priorities evolve, with written approval from both organizations. The CDC Foundation may adjust the remote arrangement as required.

Requirements

Bachelor’s degree or higher in Data Science, Statistics, Epidemiology, or a related field.
At least 5 years of relevant professional experience.
Proficiency in data visualization tools such as Power BI.
Proficiency in ArcGIS software suites.
Proficiency in statistical packages such as SAS.
Proficiency in programming languages such as Python or R.
Experience with data manipulation and analysis tools such as SQL.
Experience applying Natural Language Processing techniques for text classification or information extraction; healthcare or public health text data experience is preferred.
Experience with small area estimation techniques, Bayesian hierarchical models, or multilevel modeling.
Strong analytical thinking and problem-solving abilities.
Ability to interpret complex datasets and derive meaningful insights.
Excellent verbal and written communication skills.
Ability to explain technical concepts effectively to non-technical partners.
Flexibility to adapt to changing project requirements and priorities.
Strong interpersonal and teamwork skills, including the ability to develop productive relationships with colleagues and partners.
Ability to work independently and within teams.
Experience working in a virtual environment with remote partners and teams.
Proficiency in Microsoft Office.

Nice To Haves

A Master’s or PhD in a related field.
Experience with cloud-based data warehouses such as Snowflake and cloud platforms such as AWS or Azure.
Professional certifications in data science, machine learning, or public health analytics.

Responsibilities

Develop, implement, and improve data analysis and visualization tools that provide staff with timely, relevant information for public health decisions, including outbreak response, surveillance, and preparedness.
Analyze diverse public health datasets to identify trends, patterns, and correlations.
Apply statistical methods and machine learning algorithms to extract actionable insights.
Develop predictive models to anticipate disease patterns, assess risk factors, and guide intervention strategies.
Use statistical modeling to produce reliable, precise estimates for small populations or sparsely populated rural regions, and build interactive dashboards for real-time surveillance.
Provide geospatial analysis support for infectious disease surveillance and epidemiologic investigations.
Apply Natural Language Processing techniques to unstructured data to automate data processing and support case detection.
Continuously optimize algorithms for accuracy and performance.
Create visualizations and reports that communicate findings to partners and decision-makers.
Present data-driven insights clearly to facilitate informed decision-making.
Collaborate with the public health organization and its partners to understand data needs and objectives.
Provide data-driven support and guidance for public health policies and initiatives.
Stay informed about emerging trends, technologies, and methodologies in data science and analytics.
Explore innovative approaches to complex public health challenges and improve data analysis capabilities.
Train and provide technical assistance to staff epidemiologists in data visualization, geospatial analysis, and data analysis, including use of Power BI, ArcGIS, and SAS.