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Entry Level Genomics Data Scientist Jobs (NOW HIRING)

GRAIL

Senior Data Scientist #4887

Menlo Park, CA

$187K/yr

In this role you will work with population-scale genomic datasets from our on-market commercial ... Ph.D. in Bioinformatics, Data Science, Computational Biology, Physics, Bioengineering, Cancer ...

GRAIL

Senior Data Scientist #4887

Menlo Park, CA

$187K/yr

In this role you will work with population-scale genomic datasets from our on-market commercial ... Ph.D. in Bioinformatics, Data Science, Computational Biology, Physics, Bioengineering, Cancer ...

GRAIL

Senior Data Scientist #4887

Menlo Park, CA · On-site

$187K/yr

In this role you will work with population-scale genomic datasets from our on-market commercial ... Ph.D. in Bioinformatics, Data Science, Computational Biology, Physics, Bioengineering, Cancer ...

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Entry Level Genomics Data Scientist information

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$37.5K

$122.7K

$196.5K

How much do entry level genomics data scientist jobs pay per year?

As of Jul 14, 2026, the average yearly pay for entry level genomics 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.

How to become a genomic data scientist?

To become a genomic data scientist, one typically needs a bachelor's degree in bioinformatics, genetics, computer science, or a related field, followed by gaining skills in programming languages like Python or R, and experience with genomic data analysis tools. Advanced roles often require a master's or Ph.D. in a relevant discipline and familiarity with high-throughput sequencing technologies and statistical methods. Building a strong foundation in biology, data analysis, and computational skills is essential for success in this field.

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

AspectEntry Level Genomics Data ScientistEntry Level Bioinformatics Analyst
Required CredentialsBachelor's in Bioinformatics, Genetics, or related field; some roles prefer internshipsBachelor's in Bioinformatics, Biology, or related field; similar certifications
Work EnvironmentResearch labs, biotech companies, healthcare institutionsResearch institutions, biotech firms, academic settings
Industry UsageGenomics research, personalized medicine, biotech developmentGenomics, molecular biology, clinical research
Common Search/ComparisonYesYes

Both roles require similar educational backgrounds and work in genomics-related environments. The main difference is that a Genomics Data Scientist focuses more on analyzing large genomic datasets and developing models, while a Bioinformatics Analyst often performs data processing and interpretation tasks. Understanding these distinctions helps job seekers identify the best fit for their skills and career goals.

Is 40 too late for data science?

Entry level genomics data scientists can start at age 40, as the field values relevant skills such as programming, statistical analysis, and knowledge of genomics tools. Many professionals successfully transition into data science later in their careers by gaining certifications and practical experience, making age less of a barrier than skill set and dedication.

Can I get a data scientist job with no experience?

Entry-level genomics data scientist positions typically require some foundational knowledge in biology, programming, and data analysis, but they often do not require extensive professional experience. Candidates can improve their chances by gaining skills in tools like Python, R, and bioinformatics software, and obtaining relevant certifications or completing internships. Demonstrating a strong understanding of genomics concepts and analytical skills can help entry-level applicants secure such roles.

How do I become a data scientist with no experience?

To become an entry-level genomics data scientist with no experience, focus on building foundational skills in programming (such as Python or R), statistics, and biology through online courses or tutorials. Gaining practical experience with datasets, learning relevant tools like Jupyter notebooks, and obtaining certifications can improve your prospects; internships or volunteer projects also provide valuable hands-on experience.
More about Entry Level Genomics Data Scientist jobs
What cities are hiring for Entry Level Genomics Data Scientist jobs? Cities with the most Entry Level Genomics Data Scientist job openings:
What are the most commonly searched types of Genomics Data Scientist jobs? The most popular types of Genomics Data Scientist jobs are:
What states have the most Entry Level Genomics Data Scientist jobs? States with the most job openings for Entry Level Genomics Data Scientist jobs include:
What job categories do people searching Entry Level Genomics Data Scientist jobs look for? The top searched job categories for Entry Level Genomics Data Scientist jobs are:
Entry Level Genomics Data Scientist jobs near you
Infographic showing various Entry Level Genomics Data Scientist job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.
Sr. Data Scientist, Translational Research

Sr. Data Scientist, Translational Research

Tempus

Chicago, IL • On-site

Full-time

Re-posted 4 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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