Lead Data Scientist - Medicaid & Health Policy Analytics

University of Florida; Gainesville (AL); On-site; USD 98,000 - 110,000; Full time

Job summary

University of Florida's Institute for Child Health Policy seeks a Data Scientist IV to lead analytics projects evaluating Medicaid and CHIP program performance. You will manage research studies, develop analytic plans, and produce technical reports for stakeholders.

The role emphasizes expertise in healthcare administrative data, SAS/Python/R/SQL, and collaboration with health policy researchers to translate findings into actionable recommendations.

Qualifications

• A Bachelor's Degree in data science, statistics, bioinformatics, analytics, or similar field and seven years of experience.
• A Master's Degree in data science, statistics, bioinformatics, analytics, or similar field and five years of experience.
• A Doctoral Degree in data science, statistics, bioinformatics, analytics, or similar field and three years of experience.

Responsibilities

• Lead research projects evaluating healthcare quality, access, and outcomes for Medicaid populations.
• Develop data-driven insights using large healthcare administrative and clinical datasets.
• Collaborate with multidisciplinary health policy researchers and economists to produce policy-relevant analyses.
• Author technical reports, policy briefs, peer-reviewed articles, and executive summaries.

Education

Bachelor's degree in data science, statistics, bioinformatics, analytics, or similar field

Master's Degree in data science, statistics, bioinformatics, analytics, or similar field

Doctoral Degree in data science, statistics, bioinformatics, analytics, or similar field

Tools

SAS

Python

R

SQL

Job description

University of Florida's Institute for Child Health Policy seeks a Data Scientist IV to lead analytics projects evaluating Medicaid and CHIP program performance. You will manage research studies, develop analytic plans, and produce technical reports for stakeholders.

The role emphasizes expertise in healthcare administrative data, SAS/Python/R/SQL, and collaboration with health policy researchers to translate findings into actionable recommendations.