1

Biomedical Data Science Jobs in Wisconsin (NOW HIRING)

$35/hr

Currently pursuing a Master's degree in Biostatistics, Epidemiology, Health Services Research, Health Economics and Outcomes Research (HEOR), Health/Biomedical Informatics, Data Science, or a related ...

$35/hr

Currently pursuing a Master's degree in Biostatistics, Epidemiology, Health Services Research, Health Economics and Outcomes Research (HEOR), Health/Biomedical Informatics, Data Science, or a related ...

$35/hr

Currently pursuing a Master's degree in Biostatistics, Epidemiology, Health Services Research, Health Economics and Outcomes Research (HEOR), Health/Biomedical Informatics, Data Science, or a related ...

$35/hr

Currently pursuing a Master's degree in Biostatistics, Epidemiology, Health Services Research, Health Economics and Outcomes Research (HEOR), Health/Biomedical Informatics, Data Science, or a related ...

$35/hr

Currently pursuing a Master's degree in Biostatistics, Epidemiology, Health Services Research, Health Economics and Outcomes Research (HEOR), Health/Biomedical Informatics, Data Science, or a related ...

$35/hr

Currently pursuing a Master's degree in Biostatistics, Epidemiology, Health Services Research, Health Economics and Outcomes Research (HEOR), Health/Biomedical Informatics, Data Science, or a related ...

Showing results 21-40

Biomedical Data Science information

See Wisconsin salary details

$22.4K

$101.5K

$178.1K

How much do biomedical data science jobs pay per year?

As of Sep 7, 2026, the average yearly pay for biomedical data science in Wisconsin is $101,544.00, according to ZipRecruiter salary data. Most workers in this role earn between $54,788.00 and $143,818.00 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.

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

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

Infographic showing various Biomedical Data Science job openings in Wisconsin as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 13% Part Time, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $101,544 per year, or $48.8 per hour.

Summer 2027 Internship - RWE Data Scientist - Virtual

Stryker

Racine, WI • On-site, Remote

$35/hr

Temporary, Internship

Posted 5 days ago


Key responsibilities

  • Support the design and execution of observational studies using claims and other real-world data sources.

  • Assist in data extraction, cleaning, and analysis of structured and unstructured healthcare data, including applying NLP techniques.

  • Build and refine statistical models such as propensity matching and survival analysis under mentorship.


Stryker rating

8.2

Company rating: 8.2 out of 10

Based on 112 frontline employees who took The Breakroom Quiz

134th of 499 rated machine equipment manufacturers


Job description

What You Get Out of the Internship

At Stryker, we believe that developing the next generation of talent is just as important as developing life-changing medical technologies. As an intern, you won’t just observe — you’ll contribute to meaningful projects, gain exposure to leaders who will mentor you, and experience a culture of innovation and teamwork that is shaping the future of healthcare. As an intern, you will:

  • Apply classroom knowledge and gain experience in a fast-paced and growing industry setting
  • Implement new ideas, be constantly challenged, and develop your skills
  • Network with key/high-level stakeholders and leaders of the business
  • Be a part of an innovative team and culture
  • Experience documenting complex processes and presenting them in a clear format

Who We Want

Challengers. People who seek out the hard projects and work to find just the right solutions.

Teammates. Partners who listen to ideas, share thoughts and work together to move the business forward.

Charismatic networkers. Relationship-savvy people who intentionally make connections with both internal partners and external contacts.

Strategic thinkers. Interns who propose innovative ideas and consistently exceed their performance objectives.

Customer-oriented achievers. Individuals with an unparalleled work ethic and customer-focused attitude who bring value to their partnerships.

Game changers. Persistent interns who will stop at nothing to live out Stryker’s mission to make healthcare better.

Opportunities Available

As a Real-World Evidence Data Science intern at Stryker, you will:

  • Work cross functionally with different departments including Clinical Affairs, Health Economics & Outcomes Research (HEOR), Regulatory Affairs, and Marketing to support real-world evidence generation programs
  • Assist in the design and execution of observational studies using claims (e.g., Premier PINC AI, NIS) and other real-world data sources
  • Support data extraction, cleaning, and analysis of structured and unstructured healthcare data, including applying NLP techniques to unstructured billing/clinical data
  • Prepare literature review summaries and evidence syntheses to support publication and regulatory submission efforts
  • Build and refine statistical models (e.g., propensity matching, survival analysis) under the mentorship of the RWE Research team
  • Shadow cross-functional team meetings to gain exposure to how RWE informs regulatory, reimbursement, and commercial strategy

What You Need

Required:

  • Currently pursuing a Master’s degree in Biostatistics, Epidemiology, Health Services Research, Health Economics and Outcomes Research (HEOR), Health/Biomedical Informatics, Data Science, or a related quantitative field; must remain enrolled in a degree-seeking program after the internship
  • Cumulative 3.0 GPA or above (verified at time of hire)
  • Must be legally authorized to work in the U.S. and not require employment-based sponsorship now or in the future
  • Proficiency in SQL and at least one statistical/analytical programming language (Python or R)
  • Coursework or applied project experience with observational/real-world data (claims, EHR, or registry data)
  • Strong written and verbal communication skills, with proven ability to collaborate and build relationships
  • Demonstrated leadership, problem-solving, and organizational skills with the ability to manage multiple priorities
  • Proficiency in Microsoft Office (Excel, Word, PowerPoint) and eagerness to learn in a dynamic environment

Preferred:

  • Prior exposure to claims databases (Medicare, MarketScan, Premier PINC AI, Optum) or EHR data structures
  • Familiarity with causal inference methods (propensity score matching, instrumental variables) and/or survival analysis
  • Experience with NLP applied to unstructured healthcare text
  • Prior coursework, thesis, or practicum work in a medtech, pharma, or payer setting

$20 min hourly wage – $35 max hourly wage, sign-on bonus, 11 paid holidays annually, and either paid corporate housing or a living stipend, dependent upon hiring location

Stryker is a global leader in medical technologies and, together with its customers, is driven to make healthcare better. The company offers innovative products and services in MedSurg, Neurotechnology, Orthopaedics and Spine that help improve patient and healthcare outcomes. Alongside its customers around the world, Stryker impacts more than 150 million patients annually.


What Stryker employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom