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# Visiting Research Data Scientist - Illinois Fire Service Institute

- **Company:** University of Illinois
- **Location:** Urbana, IL, United States
- **Salary:** $80,000.0 - $95,000.0
- **Contract:** Temporary contract
- **Skills:** Bioinformatics, Computational Biology, Databases, Data Cleansing, Data Transmissions, Data Infrastructure, Data Integration, Data Integrity, Data Security, Data Systems, Data Visualization, R (Programming Language), Python (Programming Language), Machine Learning, NumPy, RStudio, Power BI, Software Tools, SAS (Software), SciPy, SQL Databases, Computational Statistics, Tableau (Software), Data Processing, Scripting, Git, Pandas, Scikit Learn, Statistics Packages, Data Analytics, Data Management, Tools for Reporting, Software Version Control, Data Pipelines
- **Published:** July 2, 2026
- **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/17462598?backUrl=%2Fcareer%2F17462598%2FVisiting-Research-Data-Scientist-Illinois-Fire-Service-Institute-Illinois-Urbana

## About the Role

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.

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

 3. Experience with machine learning applications in health
research.

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

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

 6. 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.

## Description

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.


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