Hybrid Senior Epidemiology Data Scientist

UChicago Institute for Climate and Sustainable Growth; Chicago, Northern (IL, KY); Hybrid; USD 110,000 - 150,000; Full time

Benefits offered by this job

Hybrid work environment

Competitive salary

Benefits

Job summary

The University of Chicago invites applications for a Senior Epidemiology Data Scientist to work with Dr. Lilly Cheng-Immergluck’s lab on infectious disease prevention.

The role combines biostatistics, data analysis and study design, with responsibility for data integration, model development, and mentoring junior staff in a dynamic team. The position emphasizes collaboration with clinical data standards, external partners, and grant preparation, with a hybrid Chicago work arrangement and

Qualifications

• Minimum 7+ years of work experience in a related discipline.
• Experience analyzing large clinical datasets from public and private health sectors.
• Experience with Epic EMR system.
• Experience in developing research methods for healthcare programs.
• Experience supporting manuscript development.

Responsibilities

• Lead development of data products per PI/specifications.
• Oversee data quality control and provenance during data integration.
• Apply biostatistical methods to analyze large datasets.
• Develop infrastructure for data integration across sources (clinical, biospecimens, administrative).
• Design and evaluate statistical models and reproducible pipelines.
• Collaborate with external institutions to support data science needs.
• Interpret and visualize results for manuscripts, grants, and presentations.
• Contribute to grant applications and publications.

Skills

Biostatistics

Data analysis

Epidemiology

Machine learning

SQL

Education

Master’s degree in MPH/MS in public health/epidemiology

Tools

Epic EMR

R

SAS

SQL

Job description

The University of Chicago invites applications for a Senior Epidemiology Data Scientist to work with Dr. Lilly Cheng-Immergluck’s lab on infectious disease prevention.

The role combines biostatistics, data analysis and study design, with responsibility for data integration, model development, and mentoring junior staff in a dynamic team. The position emphasizes collaboration with clinical data standards, external partners, and grant preparation, with a hybrid Chicago work arrangement and