Data Analytics Scientist - Internal Medicine (Medical Informatics)

Collaborate with faculty investigators, clinicians, biostatisticians, informaticians, and other stakeholders to formulate research questions, hypotheses, study aims, and analytical strategies.

Contribute to the design and execution of observational studies, comparative effectiveness research, health services research, clinical research, and other data-driven investigations.

Translate scientific questions into computable phenotypes, cohort definitions, data specifications, outcome definitions, and reproducible analytical workflows.

Conduct literature reviews, feasibility assessments, preliminary analyses, and data characterization to support study development and determine the suitability of available data resources.

Collect, preprocess, integrate, clean, transform, and analyze large-scale structured and unstructured healthcare data, including EHR, claims, registry, research, and other real-world data.

Develop and apply statistical models, machine-learning algorithms, natural language processing, predictive models, and other computational methods to address biomedical and clinical research questions.

Interpret analytical findings, evaluate robustness and limitations, and communicate results effectively to investigators and both technical and non-technical stakeholders.

Contribute to scientific manuscripts, abstracts, conference presentations, technical reports, grant proposals, research protocols, statistical analysis plans, and other scholarly products.

Design, develop, optimize, and maintain scalable relational databases, research data repositories, data warehouses, data marts, and associated database schemas and data models.

Design and maintain robust ETL/ELT pipelines for extracting, integrating, harmonizing, validating, and loading large-scale healthcare datasets from heterogeneous sources.

Optimize SQL queries, database structures, indexing strategies, storage approaches, and data-processing workflows to improve performance, scalability, reliability, and maintainability.

Design, develop, test, deploy, document, and maintain production-quality software applications, APIs, analytical packages, data pipelines, and automation tools using Python, R, SQL, SAS, and other appropriate technologies.

Apply modern software engineering practices, including Git-based version control, modular design, peer code review, automated testing, CI/CD, containerization, documentation, and release management.

Participate across the software development lifecycle (SDLC) and translate research and operational requirements into scalable, secure, maintainable, and cost-effective technical solutions.

Support healthcare data interoperability and harmonization using common data models, standards, terminologies, and ontologies such as PCORnet CDM, OMOP, FHIR, HL7, UMLS, LOINC, SNOMED CT, and RxNorm, as applicable.

Implement and maintain data quality, validation, provenance, lineage, metadata, reproducibility, and change-management processes for research data and analytical products.

Ensure appropriate data security, privacy, governance, and regulatory compliance, working with investigators, IRB personnel, information security teams, and other stakeholders on HIPAA, data-use, and research requirements.

Provide technical leadership and mentorship to analysts, students, research staff, and junior technical team members, and contribute to shared standards for data architecture, software development, analytics, and research reproducibility.

Manage and contribute to the full lifecycle of multidisciplinary research and informatics projects, including planning, requirements gathering, technical design, implementation, monitoring, documentation, scientific dissemination, and continuous improvement.

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: Bachelor's degree in computer science, biomedical informatics, data science, statistics, biostatistics, mathematics, engineering, epidemiology, or a related quantitative discipline.

• This position requires a formal degree in the cited discipline area(s) to ensure that candidates have advanced knowledge, analytical skills and professional competencies necessary to perform the duties of the position. The level of degree is commonly recognized as the standard qualification for similar roles in the public and private sector, ensuring that the university remains competitive with industry aligned practices, enhances collaboration with external partners, and supports the delivery of services and programs that meet professional and market-driven expectations.

Work Experience:

• Five (5) years of experience developing, testing, debugging, documenting, and maintaining analytical software or data-processing applications.
• Experience using SQL and at least one general-purpose programming language, such as Python, R, or SAS.
• Experience with relational databases, data modeling, data warehousing, or large-scale data processing.
• Experience developing ETL/ELT workflows and integrating data from multiple sources.
• Experience applying software development practices, including version control, testing, code review, and technical documentation.
• Experience troubleshooting technical problems and developing software solutions.
• Experience using generative AI tools, including large language models or AI-assisted coding and research tools, in software development, data analysis, documentation, or research.

Preferred Qualifications

Education:

• Master's or doctoral degree in computer science, biomedical informatics, data science, statistics, biostatistics, engineering, or a related discipline.

Work Experience:

• Professional experience in data science, data engineering, software engineering, biomedical informatics, or a closely related technical field.
• Experience developing and maintaining software applications, data pipelines, or analytical solutions using Python and SQL.
• Experience working with large-scale databases or data-processing environments.
• Experience working with healthcare, clinical, biomedical, or research data.
• Experience applying software development practices, including version control, testing, documentation, and code review.

Skills

• Analytical skills
• Organizational skills
• Communication skills

Required Documents

• Resume/CV

• Cover letter

Comprehensive Benefits Package:

Coverage begins on day one for health, dental, and vision insurance and includes health expense accounts with generous employer contributions if the employee participates in a qualifying health plan. Employer-paid life insurance, long-term disability insurance, and various additional voluntary insurance plans are available. Paid time off, including vacation and sick, begins accruing upon hire, plus ten paid holidays. One paid discretionary day is available after six months of employment, and paid time off for bereavement, jury duty, military service, and parental leave is available after 12 months of employment. A retirement program with a generous employer contribution and additional voluntary retirement programs (457 or 403b) are available. https://www.kumc.edu/human-resources/benefits.html

Employee Type:
Regular

Time Type:
Full time

Rate Type:
Salary

Compensation Statement:

The pay range listed for this position is determined by our compensation program using market data and salary benchmarking. A combination of factors is considered in making compensation decisions including, but not limited to, education, experience and training, qualifications relative to the requirements of the position, and funding. At the University of Kansas Medical Center, a reasonable estimate for the starting pay range will be the minimum to midpoint of the posted range, taking into account the combination of factors listed above.

Pay Range: $80,600.00 - $120,900.00

Minimum
$80,600.00

Midpoint
$100,800.00

Maximum
$120,900.00

Application Instructions:
To learn more and apply online, please visit https://kumc.wd5.myworkdayjobs.com/en-US/kumc-jobs/job/Kansas-City-Metro-Area/Data-Analytics-Scientist---Internal-Medicine--Medical-Informatics-_JR010556 or go to https://careers.kumc.edu/ and search for position number JR010556.

Applications must be submitted directly through the KU Medical Center website to be considered for this position. Any applications submitted via email or this website will NOT be reviewed or considered.

About KU Medical Center:
The University of Kansas Medical Center's mission is to educate exceptional health care professionals through a full range of undergraduate, graduate, professional, postdoctoral and continuing education programs in the schools of Medicine, Nursing and Health Professions. KU Medical Center also advances the health sciences through world-class research programs; provides compassionate and state-of-the-art patient care in an academic medical center environment; and works with communities in every Kansas county to improve the health of Kansans. Learn more at www.kumc.edu.

Benefits:
KUMC offers a range of great benefits that support employees and eligible family members. Our health insurance benefits begin on hire date and KUMC offers other exciting benefits such as paid parental leave, generous employer retirement contributions and other resources to improve health and well-being. For more information, please visit https://www.kumc.edu/human-resources/benefits.html

Equal Employment Opportunity Statement

The University of Kansas Medical Center is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, national origin, ethnicity, ancestry, age, protected veteran or disability status, marital status, parental status, or genetic information. http://policy.ku.edu/IOA/nondiscrimination">http://policy.ku.edu/IOA/nondiscrimination

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