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Biomedical Data Science Jobs in Chicago, IL (NOW HIRING)

Qualifications Education & Experience Must have MS in statistics, biostatistics, computer science, bioinformatics, biomedical engineering, or a related field & 1 year as a data scientist leading data ...

Qualifications Education & Experience Must have MS in statistics, biostatistics, computer science, bioinformatics, biomedical engineering, or a related field & 1 year as a data scientist leading data ...

Data Science/MLOps Engineer

Chicago, IL · On-site

$118K - $141K/yr

Role : Data Science/MLOps Engineer Experience: - Min 8+ Years Location: - Chicago, IL We are ... Prior experience with clinical, biomedical, or healthcare NLP use cases * Familiarity with health ...

Data Architect, Clinical

Chicago, IL · On-site

$65.75 - $84.50/hr

Required : • Bachelor's degree in computer science, Data Engineering, Information Systems, Biomedical Informatics, Engineering, or a related field. • Minimum 10 years of experience in healthcare, ...

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Biomedical Data Science information

See Chicago, IL salary details

$25.1K

$114.1K

$200.2K

How much do biomedical data science jobs pay per year?

As of Aug 29, 2026, the average yearly pay for biomedical data science in Chicago, IL is $114,142.00, according to ZipRecruiter salary data. Most workers in this role earn between $61,585.00 and $161,661.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a biomedical data scientist?

To thrive as a Biomedical Data Scientist, you need a strong background in statistics, machine learning, programming (typically Python or R), and a solid understanding of biological or clinical data. Familiarity with bioinformatics tools, data visualization platforms, high-throughput sequencing technologies, and relevant certifications (such as in data science or bioinformatics) is commonly required. Strong problem-solving abilities, communication skills, and interdisciplinary collaboration help set top professionals apart in this field. These competencies are crucial for extracting meaningful insights from complex biomedical data, driving research innovation, and supporting evidence-based healthcare decisions.

How does a biomedical data scientist typically collaborate with clinicians and researchers on interdisciplinary projects?

Biomedical Data Scientists often work closely with clinicians, biologists, and other researchers to translate complex biomedical questions into data-driven solutions. This collaboration usually involves regular meetings to understand clinical needs, define project goals, and discuss data interpretation. Effective communication is key, as team members may have different expertise and perspectives. By collaborating, Biomedical Data Scientists help ensure that analytical methods and results are both rigorous and clinically relevant, ultimately contributing to impactful healthcare outcomes.

What is the difference between Biomedical Data Science vs Bioinformatics?

AspectBiomedical Data ScienceBioinformatics
Required CredentialsDegree in Data Science, Biostatistics, or related fields; programming skillsDegree in Bioinformatics, Computational Biology, or related fields; programming skills
Work EnvironmentResearch labs, healthcare institutions, biotech companiesResearch labs, academic institutions, biotech firms
Industry UsageAnalyzing large biomedical datasets, developing predictive modelsAnalyzing biological data, genome sequencing, gene annotation
Search & Comparison IntentHigh overlap in data analysis, healthcare applicationsFocus on biological data interpretation

Biomedical Data Science and Bioinformatics share many skills and work environments, but they differ in focus. Biomedical Data Science emphasizes analyzing large datasets and developing predictive models in healthcare, while Bioinformatics concentrates on biological data analysis, such as genome sequencing. Both roles require programming skills and are vital in biomedical research, but their specific applications and industry terminology vary.

Can you become a biomedical data scientist with a biomedical science degree?

A biomedical data scientist typically has a background in biomedical science combined with skills in data analysis, programming, and statistics. While a biomedical science degree provides a strong foundation, additional training in programming languages like Python or R and experience with data management are often necessary to qualify for such roles.

What does a biomedical data scientist do?

A biomedical data scientist analyzes complex biological and medical data to identify patterns and insights that can improve healthcare and research. They use statistical methods, machine learning, and data visualization tools to interpret data from sources like electronic health records, genomic sequences, and clinical trials, often working in interdisciplinary teams and requiring programming skills in languages such as Python or R.
Infographic showing various Biomedical Data Science job openings in Chicago, IL as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 15% Part Time, 3% Contract, and 1% Nights. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $114,142 per year, or $54.9 per hour.

Team Scientists -- Translational Data Science #MED354

Chicago, IL • On-site


The University of Chicago
Colleges, Universities, and Professional Schools • 10K+ employees

8.1

Company rating: 8.1 out of 10

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Full-time

Medical, Retirement, PTO

Re-posted 21 days ago


Job description

Description
The University of Chicago's Department of Medicine is searching for full-time faculty members on the School of Medicine track, at any rank, to join the Center for Translational Data Science, which focuses on the application of data science to research problems in biology, medicine and healthcare). We seek team scientists who will lead research focusing on: a) translational data science; b) the development of data commons, data ecosystem and other cloud computing platforms, systems and applications to support translational data science; and/or c) the development of machine learning, statistical, bioinformatics and AI algorithms to support translational data science. Other duties will include teaching and supervision of trainees and students, and scholarly activity. Academic rank and compensation are dependent upon qualifications.
This position is benefits-eligible. The University of Chicago offers a wide range of benefits programs and resources for eligible employees, including health, retirement, and paid time off. Information about the benefit offerings can be found in the Benefits Guidebook.
Prior to the start of employment, qualified applicants must have a doctoral degree or equivalent, in the following fields: Biomedical Data Science, Computer Science, Data Science, Informational Technology, Biomedical Informatics, or a related field.
We especially welcome applicants whose research is broadly focused in the areas of computer science, bioinformatics, data science, mathematics, information technology, genetics, genomics, and/or systems biology.
To be considered, those interested must apply through The University of Chicago's Academic Recruitment job board, which uses Interfolio to accept applications: http://apply.interfolio.com/163014. Applicants must upload a CV including bibliography, a cover letter, and a research statement. Review of applications will continue until the positions are filled.
For instructions on the Interfolio application process, please visit: http://tiny.cc/InterfolioHelp


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