Data Scientist - Research Administration

Department:

RI Administration

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Research Informatics

Position Title:

Data Scientist - Research Administration

Job Family Group:

Professional Staff

Job Description Summary:

The Data Scientist – Research Administration provides dedicated data science and engineering support to the Department of Surgery at the University of Kansas Medical Center. The role will focus on developing data pipelines, performing statistical and machine learning analyses, and generating high-quality research outputs using large-scale clinical datasets. This position will work closely with surgeons and researchers to translate clinical questions into data-driven insights. It is a strategic role designed to strengthen the department’s research infrastructure and competitiveness for external funding.

Job Description:

Key Roles and Responsibilities:

• Collaborate with Department of Surgery researchers to define project requirements and analytic goals

• Develop and maintain scalable data pipelines and perform ETL processes for clinical data

• Conduct statistical and machine learning analyses on large, complex healthcare datasets

• Clean, transform, and prepare high-quality analytic datasets for research

• Build and validate predictive models to support research questions and clinical insights

• Develop and maintain reusable data marts for commonly used research variables

• Document data workflows, coding processes, and analytic decisions to ensure reproducibility

• Prepare visualizations, summary reports, and presentations of research findings

• Contribute to manuscript and grant writing by providing data-related content and results

• Ensure compliance with data governance, privacy regulations, and institutional policies

This job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. It is only a summary of the typical functions of the job, not an exhaustive list of all possible job responsibilities, tasks, duties, and assignments. Furthermore, job duties, responsibilities and activities may change at any time with or without notice.

Required Qualifications

Education:

• Master’s degree in data science, computer science, biostatistics, informatics, or a related quantitative field. Education may be substituted for experience on a year for year basis. 

Work Experience:

• 2 years of experience applying statistical methods (e.g., linear/logistic regression, survival analysis in research or healthcare settings.

• 2 years of experience with data science tools and programming languages such as Python or R.

• 1 year of experience in developing and maintaining data pipelines and performing data wrangling/cleaning tasks.

• 1 year of experience working with large healthcare datasets, including electronic health records (EHR).

Preferred Qualifications

Education:

• Ph.D. in data science, biomedical informatics, computer science, biostatistics, or a related quantitative discipline. Education may be substituted for experience on a year for year basis. 

Certifications/Licenses:

• Certified Health Data Analyst (CHDA)

• Certified Specialist in Predictive Analytics

• AMIA credentials

Work Experience:

• 2 years of experience working with electronic health record (EHR) data from systems such as Epic or eClinicalWorks.

• 2 years of experience developing machine learning models (e.g., random forests, gradient boosting, neural networks) for healthcare or clinical research applications.

• 1 year of experience with high-performance computing or cloud platforms (e.g., AWS, Azure, Google Cloud).

• 1 year of experience contributing to peer-reviewed research publications or grant applications involving data analysis.

• 1 year of experience building and maintaining data marts or reusable data products for research.

Skills

• Statistical analysis using R or Python

• Data pipeline development and ETL processes

• SQL and relational database querying

• Machine learning model development and validation

• Data cleaning and wrangling

• Understanding of HIPAA and data privacy in research

• Experience with EHR sy