Public Health Data Scientist I — AI & ML

Cherokee Federal; Atlanta (GA); On-site; USD 90,000 - 95,000; Full time

Benefits offered by this job

Medical, Dental, Vision, 401K

Job summary

Cherokee Federal is seeking a Data Scientist I to provide data science, statistical, and advanced analytical support to CDC programs in Atlanta. The role focuses on extracting knowledge from structured and unstructured health data to support analysis, surveillance, visualization, and data-driven decision-making.

The position involves developing and applying ML/AI tools, collaborating with data engineers, epidemiologists, and other experts, and presenting findings to diverse audiences.

Qualifications

• Bachelor’s degree in data science, statistics, CS, health science, public health, or epidemiology; master’s degree preferred.
• Experience with statistical or advanced data analysis using multiple data sources.
• Experience with predictive or prescriptive modeling, machine learning, AI, data visualization, or related analytics.

Responsibilities

• Define and develop statistical and analytic methods for complex data science projects.
• Gather, integrate, process, and analyze data from multiple public health sources.
• Apply ML/AI, predictive, and prescriptive modeling to public health data.
• Interpret findings and translate results into actionable insights for public health programs.
• Develop, implement, and monitor analytic tools for CDC programs.
• Communicate findings to technical and non-technical audiences.
• Collaborate with epidemiologists, statisticians, computer scientists, and policy analysts on surveillance and studies.

Skills

Statistical analysis

Machine learning

Data visualization

Public health data

Data processing

Communication

Collaboration

Education

Bachelor's degree in data science or related field

Master's degree preferred

Job description

Cherokee Federal is seeking a Data Scientist I to provide data science, statistical, and advanced analytical support to CDC programs in Atlanta. The role focuses on extracting knowledge from structured and unstructured health data to support analysis, surveillance, visualization, and data-driven decision-making.

The position involves developing and applying ML/AI tools, collaborating with data engineers, epidemiologists, and other experts, and presenting findings to diverse audiences.