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Biomedical Data Science Jobs in Illinois (NOW HIRING)

Postdoctoral Fellow

Campus, IL · On-site

$47K - $64K/yr

D. in Bioinformatics, Computational Biology, Computer Science, Data Science, Statistics, Genomics, Biomedical Informatics, or a related quantitative discipline. Education and Experience Preferred:

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 ...

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 ...

Postdoctoral Fellow

Campus, IL

$47K - $64K/yr

Develop and apply AI/ML methods to biomedical data, including pipeline development (25 ... D. in either computer science, bioinformatics, quantitative science, computational biology, or ...

Research Data Scientist

Chicago, IL · On-site

$62 - $76/hr

Position Summary A part time data science position is available in the laboratory of Dr. Nicole ... biomedical professionals and the discovery of knowledge dedicated to improving wellness. The ...

Computational Biology, Biostatistics/Statistical Genetics, Bioinformatics, Biomedical Informatics, Biometrics, Data Science for Health or similar * biological or medical knowledge e.g. Cancer Biology ...

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Biomedical Data Science information

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.

What cities in Illinois are hiring for Biomedical Data Science jobs?

Cities in Illinois with the most Biomedical Data Science job openings:

Infographic showing various Biomedical Data Science job openings in Illinois as of August 2026, with employment types broken down into 6% Internship, 83% Full Time, and 11% Part Time. Highlights an 89% In-person, and 11% Remote job distribution.

Team Scientists -- Translational Data Science #MED354

University of Chicago

Chicago, IL • On-site

Full-time

Re-posted 29 days ago


University Of Chicago rating

8.1

Company rating: 8.1 out of 10

Based on 47 frontline employees who took The Breakroom Quiz

171st of 631 rated colleges and universities


Job description

Job Summary:
The University of Chicago's Department of Medicine is searching for full-time faculty members to join the Center for Translational Data Science. The role focuses on leading research in translational data science and developing systems and algorithms to support this field.
Responsibilities:
• lead research focusing on translational data science
• development of data commons, data ecosystem and other cloud computing platforms, systems and applications to support translational data science
• development of machine learning, statistical, bioinformatics and AI algorithms to support translational data science
• teaching and supervision of trainees and students
• scholarly activity
Qualifications:
Required:
• Doctoral degree or equivalent in Biomedical Data Science, Computer Science, Data Science, Informational Technology, Biomedical Informatics, or a related field.
• Experience in translational data science.
• Experience in the development of data commons, data ecosystem and other cloud computing platforms, systems and applications to support translational data science.
• Experience in the development of machine learning, statistical, bioinformatics and AI algorithms to support translational data science.
• Ability to teach and supervise trainees and students.
• Engagement in scholarly activity.
Preferred:
• Research broadly focused in the areas of computer science, bioinformatics, data science, mathematics, information technology, genetics, genomics, and/or systems biology.
Company:
University of Chicago is a world-renowned, private research university located in Chicago. Founded in 1890, the company is headquartered in Chicago, USA, with a team of 10001+ employees. The company is currently Late Stage.

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