Data Scientist

e3932d5d-76d7-4cf9-8aa5-0c23d5c4dbac•Delaware, DE

11h•$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. Working within the Delaware Division of Public Health Epidemiology Section, the position will derive insights supporting outbreak response, surveillance, and preparedness, including measles, and contribute to improvements in data and information systems. The Data Scientist will be employed by the CDC Foundation and assigned to the Delaware Division of Public Health Epidemiology Section. The position is remote and requires the employee to be based in the United States. It is part-time at 20 hours per week, with an end date of March 31, 2027. The listed salary is $44.57–$64.55 per hour, plus benefits. The remote arrangement may be adjusted by the CDC Foundation. Relocation expenses are not included. This role is part of a dynamic public health program, so responsibilities may change as circumstances and priorities evolve. Duties may be expanded or updated with written approval from both the CDC Foundation and the Delaware Division of Public Health.

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 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 evolving project requirements and priorities.
Strong interpersonal and teamwork skills, with the ability to build productive relationships with colleagues and partners.
Ability to work independently and as part of a team.
Experience working remotely with virtual partners and teams.
Proficiency in Microsoft Office.

Nice To Haves

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 derive actionable insights.
Develop predictive models to anticipate disease patterns, assess risk factors, and guide intervention strategies.
Use statistical modeling techniques 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 to unstructured data to automate data processing and support case detection.
Continuously optimize algorithms to improve accuracy and performance.
Create visualizations and reports that communicate findings to partners and decision-makers.
Present data-driven insights clearly to support 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.