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Virtual Bioinformatics Data Scientist Jobs in Utah

micro1 AI

Bioinformatics Software Engineer

Provo, UT · Remote

$80 - $110/hr

Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance ... or virtual screening workflows. * Comfort working with public chemical and bioactivity databases ...

University of Utah

Bioinformatics Management

Salt Lake City, UT · Hybrid

$110K - $122K/yr

  • Medical

  • Retirement

... data management consultation, initial project intake, and scientific navigation. 4. Cross-Domain ... Senior Manager, Bioinformatics: Requires a bachelor's (or equivalency) + 8 years or a master's (or ...

University of Utah

Bioinformatics Management

Salt Lake City, UT · On-site

$110K - $122K/yr

  • Medical

  • Retirement

... data management consultation, initial project intake, and scientific navigation. 4. Cross-Domain ... Senior Manager, Bioinformatics: Requires a bachelor's (or equivalency) + 8 years or a master's (or ...

micro1 AI

Digital Chemistry Specialist - Remote

Provo, UT · Remote

$90 - $120/hr

Bioinformatics Scientist Role Type: Contractor Location: Remote micro1 is engaging Bioinformatics ... Evaluate and synthesize findings from biological, chemical, and clinical data sources. * Offer ...

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Virtual Bioinformatics Data Scientist information

What is a virtual bioinformatics data scientist?

A Virtual Bioinformatics Data Scientist is a professional who analyzes and interprets complex biological data, such as genomic sequences, using computational tools and statistical techniques, often working remotely. They collaborate with researchers and healthcare professionals to process large datasets, develop algorithms, and extract meaningful insights that advance scientific or clinical research. The 'virtual' aspect means they perform their duties online, leveraging cloud platforms and remote collaboration tools. This role requires expertise in biology, computer science, and data analytics. Their work supports advancements in fields like personalized medicine, drug development, and genomics.

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

To thrive as a Virtual Bioinformatics Data Scientist, you need a strong background in biology, statistics, and computer science, often supported by an advanced degree in bioinformatics or a related field. Proficiency in programming languages like Python or R, experience with bioinformatics tools (e.g., BLAST, GATK), and familiarity with cloud computing platforms are typically required. Outstanding analytical thinking, collaboration, and effective communication skills set top performers apart in this field. These competencies are crucial for extracting meaningful insights from complex biological data and facilitating impactful research in a remote, interdisciplinary environment.

How does a virtual bioinformatics data scientist typically collaborate with cross-functional teams in a remote setting?

As a Virtual Bioinformatics Data Scientist, you will regularly collaborate with biologists, clinicians, and software engineers via digital communication and project management platforms. Effective communication is crucial, as you’ll be expected to translate complex data findings into actionable insights for non-technical team members. Most virtual teams use tools like Slack, Zoom, and shared cloud-based repositories to facilitate real-time collaboration and feedback. Proactive participation in virtual meetings, clear documentation, and adaptability to asynchronous workflows are key to successful teamwork in this remote role.

What is the difference between Virtual Bioinformatics Data Scientist vs Virtual Bioinformatics Analyst?

AspectVirtual Bioinformatics Data ScientistVirtual Bioinformatics Analyst
Required CredentialsTypically requires a master's or Ph.D. in bioinformatics, computational biology, or related fieldsUsually holds a bachelor's or master's degree in bioinformatics, biology, or related areas
Work EnvironmentConducts complex data modeling, algorithm development, and predictive analyticsFocuses on data interpretation, report generation, and supporting research teams
Employer & Industry UsageUsed in biotech, pharmaceutical, and research institutions for advanced data analysisCommon in research labs, healthcare, and biotech companies for data support roles

The Virtual Bioinformatics Data Scientist and Virtual Bioinformatics Analyst roles share overlapping skills but differ mainly in complexity and focus. Data scientists handle advanced modeling and algorithm development, often requiring higher credentials, while analysts focus on data interpretation and reporting. Both roles are vital in biotech and research industries, but their responsibilities and expertise levels vary.

What are the most commonly searched types of Bioinformatics Data Scientist jobs in Utah?

The most popular types of Bioinformatics Data Scientist jobs in Utah are:

What cities in Utah are hiring for Virtual Bioinformatics Data Scientist jobs?

Cities in Utah with the most Virtual Bioinformatics Data Scientist job openings:

Virtual Bioinformatics Data Scientist jobs near you

Bioinformatics Software Engineer

micro1 AI

Provo, UT • Remote

$80 - $110/hr

Part-time

Posted 16 days ago

Job description

Role Title: Computational Biology & Cheminformatics Expert


Role Type: Contractor


Location: Remote


micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their expertise to a customer’s computational drug discovery 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 and interpret small-molecule and drug discovery datasets using advanced computational biology, bioinformatics, and cheminformatics methods.
  2. Curate, annotate, and validate chemical and biological datasets (e.g., ChEMBL, PubChem, DrugBank) to support AI-driven discovery platforms.
  3. Evaluate compound-target interactions, ADMET properties, and lead optimization strategies by integrating chemical, biological, and clinical data sources.
  4. Provide expert insights on structure-activity and structure-property relationships (SAR/SPR), medicinal chemistry approaches, and experimental design considerations.
  5. Build and implement code-based benchmark tasks (e.g., terminal/CLI-based environments) that reflect realistic computational drug discovery scenarios.
  6. Develop reproducible environments (e.g., using Docker) and automated testing pipelines to ensure task correctness and solvability.
  7. Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance, delivering detailed written feedback and recommendations.


Preferred Qualifications

  1. Advanced expertise in Computational Biology, Cheminformatics, Medicinal Chemistry, Biochemistry, or related fields; advanced degree (PhD, MSc, PharmD) highly valued but not strictly required.
  2. Strong coding proficiency in Python (beyond analysis scripts), with hands-on experience building tools, pipelines, or testable code; familiarity with Git, GitHub, and Docker.
  3. Extensive experience with cheminformatics toolkits and platforms such as RDKit, KNIME, Schrödinger, OpenEye, or MOE.
  4. Proven track record in small-molecule drug discovery, SAR/QSAR evaluation, ADMET prediction, or virtual screening workflows.
  5. Comfort working with public chemical and bioactivity databases and integrating diverse datasets for scientific analysis.
  6. Demonstrated ability to clearly communicate complex chemical and biological concepts in written feedback and reports.
  7. Experience participating in multidisciplinary and/or remote projects; familiarity with AI-assisted coding tools is a plus.

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