Senior Scientific Data Analyst – Health Surveillance (Hybrid)

Kids for the Future; Silver Spring (MD); Hybrid; USD 80,000 - 105,000; Full time

Benefits offered by this job

Health insurance

Dental

Vision

STD/LTD

Life insurance

401k match

Voluntary products

Job summary

Knowesis is seeking an SME II – Scientific Data Analyst who will provide critical data management and quantitative support to the PHCoE research and epidemiology missions. This mid‑level expert ensures the integrity of large health datasets used for surveillance and research.

You will develop data conventions, generate analytic files with SQL, clean and transform data, and create variables for analyses. You will run models to support surveillance objectives and ensure reproducibility of results.

Qualifications

• Master's degree required in Data Science, Epidemiology, Statistics, or related field.
• At least 5 years of experience managing and analyzing large health or administrative datasets.

Responsibilities

• Provide clinical research data management support, including developing conventions for naming, labeling, and storing data from multiple sources.
• Use SQL to generate analytic data files and transform variables per project requirements.
• Clean datasets, transform data structures, and create variables needed for analyses.
• Provide scientific analytical services to ensure quality, accuracy, and reproducibility of results.
• Create program syntax and run models to support surveillance and research objectives.

Skills

SQL/SAS/R

Education

Masters degree

Tools

MIP data systems

Job description

Knowesis is seeking an SME II – Scientific Data Analyst who will provide critical data management and quantitative support to the PHCoE research and epidemiology missions. This mid‑level expert ensures the integrity of large health datasets used for surveillance and research.

You will develop data conventions, generate analytic files with SQL, clean and transform data, and create variables for analyses. You will run models to support surveillance objectives and ensure reproducibility of results.