Health Data Scientist II

C001 Medical University of South Carolina (MUSC - Univ); Town of Charleston (NY); On-site; USD 39,000 - 67,000; Full time

Job summary

Medical University of South Carolina (MUSC) seeks a Programmer/Research Analyst to support cancer-related research using Medicare, Medicaid, SEER, NHANES, Optum, and EMR data. You will design datasets, build reproducible pipelines, and apply ML/AI techniques for population health studies as part of the Hollings Cancer Center team.

You will implement analytical methods for effectiveness and health services research and contribute to manuscript-ready analyses and conference presentations.

Qualifications

• Bachelor's degree with mathematics and/or statistics coursework.
• Master’s degree (minimum) in health informatics, data science, health services research, biostatistics, epidemiology, or related quantitative field.
• Experience programming with SAS, SQL, Python, R, or Stata, including building large analytic datasets.
• Strong communication skills and ability to work with a diverse research team.

Responsibilities

• Build analytic datasets and data pipelines; design reproducible workflows for large healthcare datasets.
• Develop statistical and computational code for analyses and modeling (effectiveness, cost-effectiveness, health services).
• Perform data integration, cleaning, and transformation across claims, EMR, registry, and survey data.
• Conduct descriptive and exploratory analyses; generate statistics and visuals for study design decisions.
• Conduct literature reviews and support research synthesis in cancer prevention and population health.

Skills

SAS

SQL

Python

R

Stata

Education

Bachelor's degree in mathematics or statistics

Master’s degree in health informatics or data science

Tools

SAS

SQL

Python

R

Stata

Job description

Medical University of South Carolina (MUSC) seeks a Programmer/Research Analyst to support cancer-related research using Medicare, Medicaid, SEER, NHANES, Optum, and EMR data. You will design datasets, build reproducible pipelines, and apply ML/AI techniques for population health studies as part of the Hollings Cancer Center team.

You will implement analytical methods for effectiveness and health services research and contribute to manuscript-ready analyses and conference presentations.