Data Scientist II

University of FloridaGainesville, FL
5d$78,000 - $89,000

About The Position

Data Infrastructure and Management Design, develop, and manage analytic data file systems across multiple research and quality improvement initiatives involving large, complex, and multi-source healthcare datasets. Support data warehousing processes, data integration, validation, and documentation across diverse platforms and environments. Research and Evaluation Support: Under general supervision, support the design and execution of research studies evaluating healthcare quality, access, and outcomes for the Medicaid population. Utilize healthcare administrative and clinical data to conduct analyses addressing defined research questions. Apply appropriate statistical and analytic methods, interpret results, and contribute to study documentation. Assist in preparing technical reports, policy briefs, and presentation materials summarizing findings. Statistical Analysis and Interpretation Under general supervision, apply data science and statistical software such as SAS, Python, and SQL to manage, analyze, and validate large and complex datasets. Perform data cleaning, quality checks, and routine performance measurement analyses. Develop reproducible analytic code and documentation consistent with organizational standards. Clearly communicate analytic methods, assumptions, and findings to project leads and team members. Communication & Collaboration: Demonstrate strong verbal and written communication skills. Translate analytic outputs into clear summaries for internal stakeholders. Participate in meetings with research teams and operational partners to explain results, respond to questions, and support data-informed decision-making. Seek guidance as needed while progressively building subject matter and technical expertise. Contribute to other duties as assigned.

Requirements

  • A Bachelor’s Degree in data science, statistics, bioinformatics, analytics, or similar field and three years of experience; Master’s Degree in data science, statistics, bioinformatics, analytics, or similar field and one year of experience; Doctoral Degree in data science, statistics, bioinformatics, analytics, or similar field.

Nice To Haves

  • Demonstrated proficiency in statistical analysis and programming, with experience using multiple analytic tools (e.g., SAS, R, Python, SPSS) and developing reusable, well-documented code.
  • Strong data science and management skills, including preparing analysis-ready datasets, implementing quality checks, and working with relational databases and SQL.
  • Master’s degree in a data science–related field (e.g., Computer Science, Statistics, Biostatistics, Informatics, Analytics) or equivalent advanced training.
  • Proven ability to work independently with initiative, manage competing priorities, and deliver high-quality work with minimal supervision.

Responsibilities

  • Design, develop, and manage analytic data file systems
  • Support data warehousing processes, data integration, validation, and documentation
  • Support the design and execution of research studies evaluating healthcare quality, access, and outcomes
  • Utilize healthcare administrative and clinical data to conduct analyses addressing defined research questions
  • Apply appropriate statistical and analytic methods, interpret results, and contribute to study documentation
  • Assist in preparing technical reports, policy briefs, and presentation materials summarizing findings
  • Apply data science and statistical software such as SAS, Python, and SQL to manage, analyze, and validate large and complex datasets
  • Perform data cleaning, quality checks, and routine performance measurement analyses
  • Develop reproducible analytic code and documentation consistent with organizational standards
  • Communicate analytic methods, assumptions, and findings to project leads and team members
  • Translate analytic outputs into clear summaries for internal stakeholders
  • Participate in meetings with research teams and operational partners to explain results, respond to questions, and support data-informed decision-making
  • Contribute to other duties as assigned
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