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Data Scientist - Research Administration

Job in Kansas City, Wyandotte County, Kansas, 66115, USA
Listing for: University of Kansas Medical Center
Full Time position
Listed on 2026-01-12
Job specializations:
  • IT/Tech
    Data Scientist, Data Analyst, Data Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below

Department

RI Administration
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.

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
Education

Required Qualifications

  • 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 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
  • 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
Additional Work Experience
  • 2 years of experience working with electronic health record (EHR) data from systems such as Epic or eClinical

    Works.
  • 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 systems (e.g., Epic, eClinical

    Works)
  • Familiarity with clinical data models (e.g., OMOP, PCORnet)
  • Development of advanced machine learning models (e.g., deep learning, ensemble methods)
  • Advanced Use of cloud-based data platforms or high-performance computing environments
  • Proficient Experience with data visualization tools (e.g., Tableau, Power BI, Plotly)
  • Knowledge of version control systems (e.g., Git)
  • Familiarity with research workflows and publication processes
Required Documents
  • Resume
  • Cover Letter
Comprehensive Benefits Package

Coverage begins on day one for health, dental, and vision insurance and includes…

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