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Genomic Data Scientist Jobs (NOW HIRING)

Genomics Ltd

Lead Scientist

Triangle, VA · On-site

  • Medical

  • Life

  • Retirement

  • PTO

Why We Exist Genomics is a science-led transatlantic TechBio combining large-scale genetic and health data with proprietary analytics to accelerate drug discovery and advance predictive, preventative ...

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Genomic Data Scientist information

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$37.5K

$122.7K

$196.5K

How much do genomic data scientist jobs pay per year?

As of Aug 18, 2026, the average yearly pay for genomic data scientist in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is a genomic data scientist?

Genomic Data Scientists are professionals who analyze and interpret large-scale genomic data using computational, statistical, and bioinformatics techniques. They work at the intersection of biology, computer science, and statistics to extract meaningful insights from genetic information. Their work supports research in areas such as personalized medicine, disease gene discovery, and evolutionary biology. Genomic Data Scientists often collaborate with researchers, clinicians, and other scientists to solve complex biological problems and advance scientific understanding.

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

To thrive as a Genomic Data Scientist, you need expertise in bioinformatics, statistics, and genomics, typically supported by a degree in computational biology, bioinformatics, or a related field. Familiarity with programming languages like Python or R, experience with high-throughput sequencing data analysis tools, and knowledge of genomic databases are essential. Strong problem-solving abilities, attention to detail, and effective communication skills help you interpret complex data and collaborate across disciplines. These skills are crucial for deriving actionable insights from large-scale genomic data and advancing research or clinical applications.

What are some common challenges faced by genomic data scientists when working with large-scale genomic datasets?

Genomic Data Scientists often encounter challenges related to managing and processing massive datasets, which require robust computational resources and efficient data storage solutions. Data integration from different sources and formats can also be complex, necessitating careful quality control and normalization. Additionally, ensuring reproducibility of analyses and translating raw data into actionable biological insights require strong collaboration with biologists, clinicians, and other data scientists. Staying updated with evolving tools, algorithms, and best practices is also essential for success in this rapidly changing field.
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Genomic Data Scientist jobs near you
Infographic showing various Genomic Data Scientist job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Sr. Data Scientist, Translational Research

Tempus

Chicago, IL • On-site

Full-time

Re-posted 9 days ago

Job description

Passionate about precision medicine and advancing the healthcare industry?
Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way. Tempus' proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients, at the right time.
With the advent of genomic sequencing, we can finally decode and process our genetic makeup; however, computer technology has had a limited impact in healthcare. With the expansion of multi-modal healthcare data and recent advancements in AI, that's about to fundamentally change. Tempus is a healthcare technology company at the forefront of that change, leveraging data and technology to improve patient lives.
Lens, Tempus' proprietary data and platform connect an entire ecosystem of real-world data to deliver real-time, actionable insights to researchers. Our data empowers researchers to better characterize and understand disease, and to drive better outcomes through precise, individualized care.
The Scientific and Technical Solutions team is seeking a driven, intellectually curious member to bridge the gap between our cutting-edge analytical platform and the complex research questions of our clients. This role is central to client success and adoption of the Tempus Data and the Lens Platform. You will serve as the primary technical and scientific resource, ensuring our clients can seamlessly integrate their research with our data and platform to derive meaningful, scientific answers.
Key Responsibilities:
  • Client Onboarding & Education: Lead the technical and scientific onboarding process for new clients, ensuring a smooth transition into the Tempus Data Ecosystem and our analytical platform, Lens.
  • Scientific Problem Solving: Engage with clients (primarily researchers and scientists) to deeply understand their specific scientific hypotheses and questions (e.g., biomarker discovery, target identification, clinical trial design).
  • Platform Guidance & Solutioning: Translate the client's scientific needs into actionable steps on the Tempus analytical platform. This includes designing workflows, structuring queries, and guiding the analysis of complex datasets (genomic, clinical, imaging).
  • AI-Assisted Optimization: Leverage LLMs and co-pilot tools to accelerate internal development and create specialized agents that help clients navigate and derive insights from large-scale biomedical data, and make the client experience on the platform as easy, efficient, and intuitive as possible.
  • Feedback Loop: Act as the voice of the client, collaborating closely with Tempus Product, Engineering, and Data Science teams to prioritize features and resolve technical challenges.
  • Documentation & Training: Create high-quality technical documentation, tutorials, and training materials for clients on platform features and best practices for scientific analysis.

Qualifications:
Required Skills & Experience
  • A Master's or Ph.D. in a relevant scientific field (e.g., Computational Biology, Bioinformatics, Genomics, Data Science, or a related life science discipline).
  • Demonstrated experience working with and analyzing large-scale biomedical datasets (e.g., Next-Generation Sequencing data, clinical trial data, real-world data).
  • Experience working with statistical modeling, data mining and/or machine learning methods.
  • Hands-on experience with analytical tools and languages relevant to biomedical research. Must be fluent in Python or R. If Python is the primary language, having some R coding experience is required. Being comfortable in both languages is an added bonus.
  • Experience with software development and the AWS or GCP technical stack
  • Experience with engineering practices for research computing (Docker, Git, Github, Linux, cloud computing).
  • Demonstrated proficiency with AI-assisted development tools (e.g., GitHub Copilot in VS Code) to optimize coding efficiency and troubleshooting.
  • Experience building specialized AI agents or designing workflows that utilize LLMs to solve complex technical problems.
  • Experience putting data science workflows into production.
  • Proven ability to work collaboratively in a team environment and thrive in a fast-paced environment, willing to shift priorities seamlessly.
  • Demonstrated "power-user" proficiency with AI-assisted development tools (e.g., GitHub Copilot in VS Code) to optimize coding efficiency and troubleshooting.
  • Excellent written and verbal communication skills with a proven ability to explain complex technical and scientific concepts to both technical and non-technical audiences.
  • A strong track record of identifying inefficiencies or scientific roadblocks and developing pragmatic, user-friendly solutions.

Preferred (Bonus) Qualifications:
  • Experience in the biotech, pharma, or healthcare technology space.
  • Direct experience with oncology research.
  • Experience with: Pandas, NumPy, SciPy, Scikit-learn, Jupyter Notebooks, RStudio, R Package development, tidyverse, ggplot, Git, matplotlib, seaborn, HTML5, CSS3, JavaScript, D3, Plot.ly, Flask, Dask

$100,000-175,000
The expected salary range above is applicable if the role is performed from California and may vary for other locations (Colorado, Illinois, New York). Actual salary may vary based on qualifications and experience. Tempus offers a full range of benefits, which may include incentive compensation, restricted stock units, medical and other benefits depending on the position.
Additionally, for remote roles open to individuals in unincorporated Los Angeles - including remote roles- Tempus reasonably believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment: engaging positively with customers and other employees; accessing confidential information, including intellectual property, trade secrets, and protected health information; and appropriately handling such information in accordance with legal and ethical standards. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.
We are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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