MS degree with up to 5 years of experience or BA/BS with 5-10 years of experience in a relevant field.
Experience working with CDC staff across multiple organizational levels.
Proficiency in SQL, R, Python, or SAS for data manipulation and analysis.
Experience with large datasets, preferably in public health or healthcare contexts.
Familiarity with cloud platforms and data cleaning techniques.
Responsibilities
Support management of respiratory hospitalization surveillance datasets such as COVID-19 and RSV.
Clean and merge datasets from various sources to enhance consistency.
Perform routine data validation checks to ensure data accuracy and integrity.
Collaborate with other epidemiologists to maintain data quality standards.
Document and track data changes while updating data dictionaries as necessary.
Benefits
Travel opportunities as required to fulfill job duties.
Gain experience in a high-impact public health environment.
Collaborate with experienced professionals in epidemiology and public health.
Opportunity to contribute to meaningful public health surveillance.
Full Job Description
Job Type
Full-time
Description
ANTICIPATED START DATE: 2 weeks after candidate identification
TRAVEL: As required to fulfill the responsibilities of the position
Epidemiologist III will provide technical assistance to support regional capacity to conduct surveillance, detection, and response to events of public health significance.
Support management and organization of respiratory hospitalization surveillance datasets (e.g., COVID-19, RSV).
Clean, merge, and maintain datasets from multiple sources to ensure consistency and usability.
Assist in aligning variables, standardizing naming conventions, and reconciling discrepancies across datasets and time.
Perform routine data validation checks to identify missing, inconsistent, or out-of-range values.
Generate and maintain basic QA reports and track data issues and resolutions.
Contribute to the development and upkeep of data dictionaries and metadata documentation.
Assist in drafting and maintaining standard operating procedures (SOPs) for data workflows.
Support data ingestion, transformation, and preparation for analysis and reporting.
Create simple, user-friendly summaries or guides to support data users and stakeholders.
Collaborate with epidemiologists and team members to ensure data quality and consistency.
Maintain data security and confidentiality in accordance with project requirements.
Work with structured and semi-structured datasets across platforms (e.g., Excel, SQL, REDCap, or cloud environments).
Perform data cleaning, transformation, and basic harmonization tasks.
Support merging of datasets and validation of outputs.
Assist in tracking and documenting changes in data structure over time.
Execute predefined QA checks and flag data quality issues.
Maintain logs of data issues, corrections, and updates.
Update data dictionaries and documentation as datasets evolve.
Follow established data governance and documentation standards.
Requirements
MS with 0-5+ years' experience or BA/BS with 5-10+ years' experience.
Desired Qualifications
Experience working with CDC staff at multiple organizational levels.
Proficiency in at least one: SQL, R, Python, or SAS.
Experience working with large datasets (public health or healthcare data preferred).
Familiarity with Excel and data cleaning techniques.
Exposure to cloud platforms (e.g., Databricks) or willingness to learn.
Basic understanding of data validation and QA processes.
Communicate data issues and findings clearly to team members.
Work collaboratively with technical and non-technical stakeholders.
Follow established processes and escalate issues when needed.
Exposure to public health or surveillance data systems.
Experience with basic automation or scripting for data checks.
Familiarity with metadata, data dictionaries, or documentation practices.
Introductory experience with AI-assisted tools for data review or validation.
Detail-oriented with strong organizational skills.
Able to follow structured processes and maintain consistency.
Comfortable working with moderately complex datasets.
Proactive but able to work within defined guidance and frameworks.
