Clinical Data Research Analyst — SQL & R

University of Kansas Medical Center; United States; On-site; USD 65,000 - 100,000; Full time

Benefits offered by this job

Health insurance

Dental & vision insurance

Paid time off

Retirement plan

Job summary

The University of Kansas Medical Center, SOM KC Internal Medicine - Medical Informatics, invites applications for a Research Analyst to access and analyze data from EHRs, claims, and public datasets to create analysis-ready datasets and support publications and grant proposals.

You will use SQL, R or SAS to perform analyses, document data extraction processes, and develop tutorials and reusable tools for teaching initiatives in collaboration with faculty.

Qualifications

• Master's degree in Biostatistics/Statistics, Epidemiology, Quantitative Methods, or related field.
• Two years direct work experience in analysis of clinical databases (e.g., EHRs, claims databases, clinical research networks and large datasets).
• Demonstrated ability with SQL and R, or SAS.

Responsibilities

• Create custom analysis-ready datasets from structured and unstructured clinical research data repositories and databases.
• Use SQL, R or SAS to perform data analysis.
• Assist in the preparation of statistical analysis plans, analyses and create statistical analysis reports.
• Maintain detailed documentation of data extraction and analysis supporting publications and grant proposals.
• Create user-friendly documentation, reusable data processing and analysis tools and materials for faculty teaching initiatives.
• Other duties as assigned.

Education

Master's degree in Biostatistics/Statistics or related field

Tools

SQL

R

SAS

Job description

The University of Kansas Medical Center, SOM KC Internal Medicine - Medical Informatics, invites applications for a Research Analyst to access and analyze data from EHRs, claims, and public datasets to create analysis-ready datasets and support publications and grant proposals.

You will use SQL, R or SAS to perform analyses, document data extraction processes, and develop tutorials and reusable tools for teaching initiatives in collaboration with faculty.