Visiting Research Data Scientist - Illinois Fire Service Institute

Research Data Scientist - Illinois Fire Service Institute Illinois Fire Service Institute Join an interdisciplinary research team conducting a longitudinal study of biological responses to occupational exposures among firefighters. This research integrates diverse data sources, including health questionnaires, exposure assessments, body composition measures, biomarkers of exposure (e.g., PFAS, PAHs, and heavy metals), and biomarkers of biological effect (e.g., inflammation and oxidative stress).

The Research Data Scientist will lead data integration, data management, and advanced statistical and computational analyses to evaluate exposure-response relationships. The successful candidate will develop and implement analytical approaches that address confounding, bias, missing data, and other methodological challenges common to observational and longitudinal research.

This position offers the opportunity to contribute to high-impact occupational and environmental health research with the potential to improve firefighter health, inform exposure prevention strategies, and advance cancer prevention efforts through rigorous, data-driven science., Data Management and Integration

• Integrate, manage, and curate complex, multi-source datasets, including survey data, occupational and environmental exposure data, physiological measurements, biomarker and laboratory assay data, and clinical and longitudinal research data.
• Develop and maintain secure, organized, and scalable data infrastructure for longitudinal research studies.
• Design and maintain reproducible data pipelines, workflows, and comprehensive documentation.
• Develop and maintain data dictionaries, codebooks, metadata documentation, and standard operating procedures.
• Perform data cleaning, validation, quality control, and auditing procedures to ensure data integrity and consistency.
• Coordinate data integration across multiple research platforms and collaborating institutions.
• Establish reproducible analytical workflows using version control and best practices in computational research.

Statistical & Computational Analysis

• Perform statistical analyses of longitudinal, repeated-measures, and complex observational datasets.
• Apply advanced statistical, multivariate, and machine learning methods, including regression modeling, mixed-effects models, clustering, dimensionality reduction, predictive modeling, and classification algorithms.
• Identify, model, and interpret relationships between occupational or environmental exposures and biological responses.
• Address confounding, bias, and missing data using appropriate analytical approaches, sensitivity analyses, and model diagnostics.
• Develop analytic strategies for biomarker, epidemiologic, and translational research studies.
• Generate high-quality statistical summaries, figures, tables, and visualizations for scientific publications, presentations, and reports.
• Assist investigators with interpretation and communication of analytical findings.

Collaboration & Research Support

• Collaborate closely with investigators and multidisciplinary research teams to translate scientific questions into rigorous analytical plans.
• Support preparation of manuscripts, conference abstracts, technical reports, and peer-reviewed publications.
• Contribute to grant proposals through preliminary analyses, data visualization, and methodological input.
• Participate in study meetings and scientific discussions regarding study design, analytical strategies, and interpretation of results.
• Coordinate with laboratory personnel, statisticians, clinicians, and external collaborators regarding data transfer, formatting, and harmonization.
• Ensure compliance with IRB requirements, HIPAA regulations, data-use agreements, institutional data governance policies, and human-subjects research protections.

Data Systems & Automation

• Develop automated scripts and computational workflows to improve efficiency, reproducibility, and scalability of data processing and analysis.
• Support maintenance and optimization of REDCap databases and related data management systems.
• Build and maintain dashboards, reporting tools, and data visualization platforms as needed.
• Implement version control and reproducible research practices using platforms such as Git/GitHub.
• Assist in developing infrastructure for secure data storage, sharing, and collaborative analysis.

1. Master’s degree or PhD in Data Science, Biostatistics, Bioinformatics, Epidemiology, Computational Biology, Statistics, or a related quantitative field.

2. Experience handling and managing sensitive and confidential human-subjects data.

3. Proficiency in statistical programming languages such as R, Python, SAS, and SQL.

4. Experience analyzing longitudinal, repeated-measures, or large-scale observational datasets.

5. Experience developing clear data visualizations for technical and non-technical audiences.

6. Strong foundation in statistical modeling and inference.

7. Proficiency with REDCap database management and data quality workflows.

8. Ability to communicate effectively with a wide range of audiences.

Technical Skills

1. R/RStudio

2. Python (Pandas, NumPy, SciPy, scikit-learn)

3. SQL databases
4. REDCap
5. Tableau or Power BI
6. Git/GitHub

7. Statistical modeling and data visualization packages, 1. Experience working with biomarker, clinical, or environmental exposure data.

8. Knowledge of methods used to address confounding, bias, and missing data in observational studies.

9. Experience with machine learning applications in health research.

10. Experience integrating heterogeneous data sources across research platforms or collaborating institutions.

11. Proficiency with SQL, database systems, and/or data engineering tools.

12. Experience implementing reproducible research practices using Git or other version control systems.

Knowledge, Skills, and Abilities:

1. Strong organizational skills and attention to detail.

2. Ability to work independently and collaboratively in a multidisciplinary research environment.

This is a 100% full-time Academic Professional position, appointed on a 12-month basis. The expected start date is as soon as possible after August 16, 2026. The budgeted salary range for the position is $80,000 to $95,000. Salary is competitive and commensurate with qualifications and experience, while also considering internal equity. This position is eligible for sponsorship for work authorization, except for sponsorship of a new H1B petition that would incur the $100,000 fee. Application Procedures & Deadline Information, This position is intended to be eligible for benefits. This includes Health, Dental, Vision, Life Insurance, a Retirement Plan, Paid time Off, and Tuition waivers for employees and dependents.

At the University of Illinois Urbana-Champaign - the state’s flagship public university and one of the world’s leading research institutions - every staff member helps shape what’s next. Founded in 1867, Illinois is home to a vibrant community of 59,000 students from all 50 states and 129 countries, supported by 15 colleges and instructional units, more than 20 research institutes, and one of the most comprehensive student service ecosystems in the nation. Whether you’re empowering first-generation students, fueling breakthrough innovation, or strengthening communities across Illinois and beyond, your work here has a far-reaching and deeply meaningful impact. The university offers a highly competitive benefits package designed to support your well-being, growth, and financial security. Join a top 10 public university that has launched over 330 startups and continues to redefine excellence - where the Illinois Value Proposition ensures that your contributions are recognized, your potential is nurtured, and your career can thrive.

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