1

Bioinformatics Data Scientist Jobs in Colorado (NOW HIRING)

... clinical data sources. * Provide expert insights on structure-activity and structure-property ... Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance ...

... clinical data sources. * Provide expert insights on structure-activity and structure-property ... Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance ...

... clinical data sources. * Provide expert insights on structure-activity and structure-property ... Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance ...

... clinical data sources. * Provide expert insights on structure-activity and structure-property ... Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance ...

... clinical data sources. * Provide expert insights on structure-activity and structure-property ... Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance ...

... clinical data sources. * Provide expert insights on structure-activity and structure-property ... Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance ...

next page

Showing results 1-20

Bioinformatics Data Scientist information

See Colorado salary details

$39.4K

$129.1K

$206.6K

How much do bioinformatics data scientist jobs pay per year?

As of Aug 26, 2026, the average yearly pay for bioinformatics data scientist in Colorado is $129,062.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,600.00 and $143,000.00 per year, depending on experience, location, and employer.

What is a bioinformatics data scientist?

A Bioinformatics Data Scientist applies data science techniques to biological and genomic data to extract meaningful insights. They work with large datasets, develop algorithms, and use machine learning to analyze genetic sequences, protein structures, or clinical data. Their role often involves programming, statistical modeling, and data visualization to support research in healthcare, pharmaceuticals, and biotechnology. Strong skills in Python, R, and bioinformatics tools are essential, along with a solid understanding of biology and computational methods.

What types of projects does a bioinformatics data scientist typically work on within a research or healthcare team?

Bioinformatics Data Scientists often work on projects involving the analysis of large-scale genomic, proteomic, or clinical datasets to identify patterns, biomarkers, or insights that drive scientific research or patient care. You might be responsible for developing pipelines for next-generation sequencing data, creating machine learning models for disease prediction, or integrating diverse biological datasets to support research objectives. Collaboration with biologists, clinicians, and software engineers is common, and you’ll likely present findings to multidisciplinary teams. This diverse project work not only helps advance scientific understanding but also provides valuable experience that can open doors to roles in research leadership or applied healthcare analytics in the future.

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

To thrive as a Bioinformatics Data Scientist, you need a strong background in biology, statistics, and computer science, usually supported by a degree in bioinformatics or a related field. Expertise in programming languages such as Python or R, experience with data analysis tools, and familiarity with bioinformatics platforms like BLAST or Nextflow, along with certifications in data science or genomics, are highly valued. Strong problem-solving, communication, and teamwork skills enhance your ability to work across multidisciplinary teams. These skills are important because the role demands effective interpretation of complex biological data and collaboration to drive scientific discovery and innovative healthcare solutions.

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

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

What job categories do people searching Bioinformatics Data Scientist jobs in Colorado look for?

The top searched job categories for Bioinformatics Data Scientist jobs in Colorado are:

What cities in Colorado are hiring for Bioinformatics Data Scientist jobs?

Cities in Colorado with the most Bioinformatics Data Scientist job openings:

Infographic showing various Bioinformatics Data Scientist job openings in Colorado as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, 1% Temporary, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $129,062 per year, or $62 per hour.

Scientist I, Computation Protein Design

Alta Resource Technologies, Inc.

Boulder, CO • On-site

$140K - $175K/yr

Full-time

Medical, Dental, Vision, Retirement

Re-posted 17 days ago


Job description

About the Role:

We are seeking a highly skilled Scientist I, Computation Protein Design to join our team and drive innovation in protein design and engineering through good data practices, robust analytical methods and machine learning. This role focuses on leveraging and optimizing foundational AI models to accelerate our protein engineering pipeline. The ideal candidate will have deep expertise in model fine-tuning, evaluation, and selection, with strong data engineering capabilities to support cutting-edge computational biology research.

Key Responsibilities:

Model Development

  • Fine-tune, adapt, and use foundational protein models (e.g., BoltzGen, ESM, OpenFold derivatives) for protein engineering applications     
  • Develop and implement rigorous evaluation frameworks to assess model performance, including metrics for protein structure prediction, sequence optimization, and functional property prediction
  • Conduct comprehensive benchmarking studies to identify and recommend the most suitable foundational models for various protein engineering tasks
  • Design and execute computational experiments to validate model predictions against experimental data
  • Leverage multiple information sources (including bioinformatic, structural, simulations, and experimental performance data) to improve internal models and develop agentic frameworks

Cross-functional collaboration

  • Collaborate with the Applied Biology team to translate models into actionable insights.  
  • Create technical documentation including model assumptions, equations, validation results, and recommendations.
  • Provide technical mentorship and review for junior engineers and scientists. 
  • Clearly communicate technical findings, risks and recommendations to leadership and project stakeholders. 

Data Management, Analysis and Integration

  • Contribute to developing data management systems that meet FAIR principles. 
  • Develop analysis code to support the team in analyzing experimental data.
  • Engineer data into vectorized format for MCP integration
  • Utilize experimental data to validate and improve model development. 

Required Qualifications:

  • Ph.D. in Computational Biology, Bioinformatics, Computer Science with 1-3 years of relevant industry or post-doctoral experience, or M.S. with 6+ years of relevant industry experience
  • Hands-on experience with protein foundation models such as ESM-2, ESM-3, ProteinMPNN, RFdiffusion, AlphaFold, or similar architectures
  • Knowledge of protein design software and molecular modeling tools (Rosetta, PyMOL, Chimera)
  • Demonstrated experience fine-tuning and working with large-scale machine learning models, preferably protein or biological sequence models
  • Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, JAX)
  • Experience with model evaluation methodologies, including cross-validation, performance metrics, and statistical analysis
  • Solid understanding of protein structure, function, and the principles of protein engineering
  • Experience with high-performance computing environments and GPU-accelerated computing
  • Strong communication skills and ability to work collaboratively in interdisciplinary teams
  • US Citizenship required.

Preferred, But Not Required:

  • Experience with workflow management tools (Nextflow, Snakemake, or similar)
  • Familiarity with cloud computing platforms (AWS, GCP, Azure) and containerization (Docker, Singularity)
  • Experience with distributed computing frameworks (Dask, Ray, Spark)
  • Track record of publications or contributions to open-source projects in computational biology or machine learning

What We Offer:

  • The opportunity to lead a breakthrough program redefining U.S. supply chain resilience in critical materials.
  • A mission-driven, high-trust team operating at the intersection of innovation, national security, and sustainability.
  • High Impact & Visibility: Direct interaction and reporting to executive leadership.
  • Competitive compensation and benefits package. 
    • The starting pay range for this position is $140,000 to $175,000 commensurate with educational background and work experience. 
    • Benefits including, 401(K) medical, dental, and vision plans, or equivalent, will be provided.
    • Paid parental leave, paid sick leave, flexible time off, company holidays.