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Clinical Data Science Jobs in Michigan (NOW HIRING)

2025 Fall Intern, Clinical Applications

Flint, MI ยท On-site

$14.50 - $19.50/hr

What You Can Expect The Clinical Applications Intern is responsible for providing support to the ... Pursuing a bachelor's degree in Computer Science, Information Systems, Health Informatics, Data ...

$15.25 - $20.25/hr

What You Can Expect The Clinical Applications Intern is responsible for providing support to the ... Pursuing a bachelor's degree in Computer Science, Information Systems, Health Informatics, Data ...

$13.75 - $18.50/hr

What You Can Expect The Clinical Applications Intern is responsible for providing support to the ... Pursuing a bachelor's degree in Computer Science, Information Systems, Health Informatics, Data ...

$14.25 - $18.75/hr

What You Can Expect The Clinical Applications Intern is responsible for providing support to the ... Pursuing a bachelor's degree in Computer Science, Information Systems, Health Informatics, Data ...

Showing results 21-40

Clinical Data Science information

See Michigan salary details

$17

$49

$71

How much do clinical data science jobs pay per hour?

As of Aug 12, 2026, the average hourly pay for clinical data science in Michigan is $49.83, according to ZipRecruiter salary data. Most workers in this role earn between $39.38 and $59.28 per hour, depending on experience, location, and employer.

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

To thrive as a Clinical Data Scientist, you need a solid background in statistics, data analysis, and life sciences, often supported by a degree in biostatistics, computer science, or a related field. Familiarity with programming languages like Python or R, clinical trial data management systems, and knowledge of regulatory requirements such as GCP and CDISC standards are essential. Strong attention to detail, problem-solving abilities, and effective communication skills help you interpret complex data and collaborate with clinical and research teams. These competencies are crucial for ensuring data integrity, regulatory compliance, and valuable insights that drive evidence-based healthcare decisions.

What are the typical collaborative interactions between clinical data scientists and other departments in a healthcare or pharmaceutical organization?

Clinical Data Scientists regularly collaborate with clinical research associates, statisticians, data managers, and regulatory affairs teams. These interactions are essential for ensuring high-quality data collection, analysis, and interpretation throughout clinical trials. You may participate in cross-functional meetings, contribute to protocol development, and help design data management strategies that comply with regulatory standards. Effective communication and teamwork are important skills, as much of the role involves translating technical findings into actionable insights for non-technical stakeholders.

What is clinical data science?

Clinical data science is a field that focuses on collecting, analyzing, and interpreting data from clinical trials and healthcare settings to improve patient outcomes and advance medical research. Professionals in this area use statistical methods, programming, and domain knowledge to ensure the quality and integrity of clinical data. Their work supports evidence-based decision-making in medicine and helps bring new therapies to market safely and efficiently.

What is the difference between Clinical Data Science vs Data Analyst?

AspectClinical Data ScienceData Analyst
Required CredentialsDegree in Data Science, Biostatistics, or related field; knowledge of healthcare dataDegree in Statistics, Mathematics, or related field; proficiency in data tools
Work EnvironmentHealthcare settings, research institutions, pharmaceutical companiesBusiness, finance, marketing, or healthcare organizations
Employer & Industry UsageUsed in clinical trials, healthcare research, drug developmentUsed across various industries for business insights and reporting

Clinical Data Science focuses on analyzing healthcare and clinical trial data to support medical research and drug development, often requiring specialized healthcare knowledge. Data Analysts handle a broader range of data analysis tasks across industries, emphasizing business insights. While both roles involve data manipulation and statistical skills, Clinical Data Scientists typically work within healthcare settings on complex clinical data, whereas Data Analysts serve diverse sectors with general data reporting needs.

Infographic showing various Clinical Data Science job openings in Michigan as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $103,640 per year, or $49.8 per hour.

AI Training Specialist - Life Sciences

micro1 AI

Sterling Heights, MI โ€ข Remote

$90 - $120/hr

Part-time

Posted 15 days ago


Job description

Role Title: Bioinformatics Scientist


Role Type: Contractor


Location: Remote


micro1 is engaging Bioinformatics Scientists to contribute their specialized expertise to a customer's innovative project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required โ€” your domain knowledge is what matters.


Scope of Work

  1. Analyze complex datasets related to medicinal chemistry using advanced bioinformatics methodologies.
  2. Provide detailed scientific input and content to support the development and training of AI models.
  3. Curate, annotate, and validate datasets relevant to drug discovery and molecular analysis.
  4. Evaluate and synthesize findings from biological, chemical, and clinical data sources.
  5. Offer subject matter expertise on experimental design and data interpretation within medicinal chemistry.
  6. Assess AI-generated outputs for scientific accuracy, relevance, and reliability.
  7. Deliver comprehensive written feedback and actionable recommendations for model improvement.


Preferred Qualifications

  1. Advanced degree (e.g., PhD or MSc) in Bioinformatics, Computational Biology, Medicinal Chemistry, or a related discipline.
  2. In-depth knowledge of medicinal chemistry concepts, including structure-activity relationships and drug design principles.
  3. Demonstrated experience in handling and interpreting large-scale omics or cheminformatics datasets.
  4. Familiarity with software tools, databases, and programming languages commonly used in bioinformatics (e.g., Python, R, RDKit, KNIME).
  5. Strong scientific communication skills, with the ability to clearly articulate complex ideas and technical concepts.
  6. Proven track record of contributing to research projects at the intersection of biology, chemistry, and data science.
  7. Experience collaborating in multidisciplinary or remote project environments is advantageous.