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Remote Genomics Data Scientist Jobs in Michigan (NOW HIRING)

Vervint

Director of Data Intelligence

Grand Rapids, MI · On-site +1

Director of Data Intelligence | Remote | Michigan or Minnesota Preferred Role Snapshot: * Set the ... Build and lead a high-performing team of data scientists, analysts, and engineers. * Promote a ...

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Remote Genomics Data Scientist information

How does a remote genomics data scientist typically collaborate with cross-functional research teams?

As a Remote Genomics Data Scientist, collaboration often happens through virtual meetings, shared code repositories, and cloud-based data platforms. You'll regularly interact with bioinformaticians, laboratory scientists, and clinicians to define research questions, interpret genomic data, and ensure data analysis aligns with study goals. Effective communication is key, as you'll translate complex results for non-technical stakeholders and coordinate project timelines across different locations and time zones.

What are the key skills and qualifications needed to thrive as a remote genomics data scientist, and why are they important?

To thrive as a Remote Genomics Data Scientist, you need a strong background in bioinformatics, statistics, and genomics, typically supported by an advanced degree in a relevant field. Proficiency with programming languages such as Python or R, experience with genomic data analysis tools (e.g., GATK, Bioconductor), and cloud-based data platforms are essential. Excellent problem-solving, communication, and collaboration skills help you interpret complex data and work effectively with interdisciplinary teams. These skills ensure accurate analysis, meaningful insights, and successful remote collaboration on cutting-edge genomics projects.

What is the difference between Remote Genomics Data Scientist vs Remote Bioinformatics Analyst?

AspectRemote Genomics Data ScientistRemote Bioinformatics Analyst
Required CredentialsMaster's or PhD in Genetics, Bioinformatics, or related field; experience with genomics data analysisBachelor's or Master's in Bioinformatics, Biology, or related; familiarity with bioinformatics tools
Work EnvironmentResearch labs, biotech companies, or healthcare organizations focusing on genomicsResearch institutions, healthcare, or biotech firms analyzing biological data
Industry UsagePrimarily in genomics research, personalized medicine, and biotechIn bioinformatics projects across healthcare, agriculture, and research

Remote Genomics Data Scientists focus on analyzing genomic data to uncover biological insights, often requiring advanced degrees and specialized skills. Remote Bioinformatics Analysts handle biological data analysis but may have a broader scope, including various biological datasets. Both roles are vital in biotech and healthcare industries, but the Genomics Data Scientist typically emphasizes genomic-specific expertise.

What is a remote genomics data scientist?

A Remote Genomics Data Scientist is a professional who analyzes and interprets large-scale genetic data, such as DNA sequencing, using computational and statistical methods, while working from a remote location. Their work often involves using bioinformatics tools and machine learning to identify patterns and insights in genomic datasets. This role supports research in healthcare, pharmaceuticals, and biotechnology, helping to advance personalized medicine and disease understanding. Remote Genomics Data Scientists collaborate with multidisciplinary teams and often communicate findings through reports and visualizations.
What are the most commonly searched types of Genomics Data Scientist jobs in Michigan? The most popular types of Genomics Data Scientist jobs in Michigan are:
What are popular job titles related to Remote Genomics Data Scientist jobs in Michigan? For Remote Genomics Data Scientist jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Remote Genomics Data Scientist jobs in Michigan look for? The top searched job categories for Remote Genomics Data Scientist jobs in Michigan are:
What cities in Michigan are hiring for Remote Genomics Data Scientist jobs? Cities in Michigan with the most Remote Genomics Data Scientist job openings:
Remote Genomics Data Scientist jobs near you
Infographic showing various Remote Genomics Data Scientist job openings in Michigan as of July 2026, with employment types broken down into 5% Internship, 86% Full Time, and 9% Part Time. Highlights an 100% Remote job distribution.

Digital Chemistry Specialist - Remote

micro1 AI

Ann Arbor, MI • Remote

$90 - $120/hr

Part-time

Posted 10 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 — 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.

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