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Assistant Genomics Data Scientist Jobs (NOW HIRING)

Natera is seeking an innovative and driven bioinformatics scientist to lead and conduct cutting ... Proven expertise in bioinformatics, particularly in genomics data analysis. Demonstrated expertise ...

$159K - $251K/yr

We are seeking an experienced and innovative computational scientist to perform data mining of ... Analyze, summarize, and visualize the findings from large multi-modal clinico-genomic datasets ...

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Assistant Genomics Data Scientist information

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$46K

$165K

$243.5K

How much do assistant genomics data scientist jobs pay per year?

As of Sep 3, 2026, the average yearly pay for assistant genomics data scientist in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What does an assistant genomics data scientist do?

An Assistant Genomics Data Scientist supports research and analysis by managing, processing, and interpreting large-scale genomic datasets. They use bioinformatics tools, statistical methods, and programming languages such as Python or R to help identify patterns and insights in genetic data. Their work often contributes to projects in healthcare, pharmaceuticals, or academic research, assisting senior scientists in making sense of complex biological information. Additionally, they may help maintain data pipelines and ensure the quality and integrity of genomic databases.

What are the key skills and qualifications needed to thrive as an assistant genomics data scientist?

To thrive as an Assistant Genomics Data Scientist, you need a background in bioinformatics, statistics, and molecular biology, often supported by a relevant degree. Familiarity with programming languages such as Python or R, experience with genomic databases, and knowledge of tools like BLAST and GATK are typically required. Strong analytical thinking, attention to detail, and effective communication skills help you interpret complex data and collaborate with multidisciplinary teams. These competencies are essential for accurately analyzing genomic datasets and translating findings into actionable scientific insights.

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

Assistant Genomics Data Scientists often encounter challenges related to managing and analyzing massive genomic datasets, which can require specialized computational tools and robust data storage solutions. Ensuring data quality and integrity while dealing with issues such as missing values, sequencing errors, or inconsistent formats is also common. Additionally, collaborating with interdisciplinary teams of biologists, clinicians, and senior data scientists requires strong communication skills to translate complex findings into actionable insights. Adapting to rapidly evolving technologies and staying current with best practices in bioinformatics is essential for success in this role.

What cities are hiring for Assistant Genomics Data Scientist jobs?

Cities with the most Assistant 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 Assistant Genomics Data Scientist jobs?

States with the most job openings for Assistant Genomics Data Scientist jobs include:

Sr. Data Scientist, Translational Research

Tempus

Redwood City, CA • On-site

Full-time

Re-posted 23 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.