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Biomedical Data Science Jobs in California (NOW HIRING)

The ideal candidate will be comfortable working at the intersection of AI, software engineering, data science, and biomedical research, and will bring the creativity needed to design new approaches ...

New

... biomedical applications and has a strong background in machine learning, pattern recognition, signal processing and time-series analysis. The successful candidate will join the data science team and ...

Data Scientist

Santa Cruz, CA · On-site

$130K - $170K/yr

... biomedical sensor data with a view toward medical, health, and fitness outcomes. The ideal candidate will have a strong background in machine learning and data science and a proven track record of ...

Data Scientist

Santa Cruz, CA · Remote

$130K - $170K/yr

... biomedical sensor data with a view toward medical, health, and fitness outcomes. The ideal candidate will have a strong background in machine learning and data science and a proven track record of ...

The Oncology Data Science group within Biomedical Research supports the Oncology Disease Area with computational biology, Artificial Intelligence / Machine Learning (AI/ML), and data engineering for ...

New

... biomedical applications and has a strong background in machine learning, pattern recognition, signal processing and time-series analysis. The successful candidate will join the data science team and ...

Data Scientist

Sunnyvale, CA · On-site

$184K - $210K/yr

... biomedical applications and has a strong background in machine learning, pattern recognition, signal processing and time-series analysis. The successful candidate will join the data science team and ...

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Showing results 1-20

Biomedical Data Science information

See California salary details

$24K

$108.9K

$190.9K

How much do biomedical data science jobs pay per year?

As of Jun 12, 2026, the average yearly pay for biomedical data science in California is $108,894.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,753.00 and $154,228.00 per year, depending on experience, location, and employer.

What is the difference between Biomedical Data Science vs Bioinformatics?

AspectBiomedical Data ScienceBioinformatics
Required CredentialsDegree in Data Science, Biostatistics, or related fields; programming skillsDegree in Bioinformatics, Computational Biology, or related fields; programming skills
Work EnvironmentResearch labs, healthcare institutions, biotech companiesResearch labs, academic institutions, biotech firms
Industry UsageAnalyzing large biomedical datasets, developing predictive modelsAnalyzing biological data, genome sequencing, gene annotation
Search & Comparison IntentHigh overlap in data analysis, healthcare applicationsFocus on biological data interpretation

Biomedical Data Science and Bioinformatics share many skills and work environments, but they differ in focus. Biomedical Data Science emphasizes analyzing large datasets and developing predictive models in healthcare, while Bioinformatics concentrates on biological data analysis, such as genome sequencing. Both roles require programming skills and are vital in biomedical research, but their specific applications and industry terminology vary.

How does a Biomedical Data Scientist typically collaborate with clinicians and researchers on interdisciplinary projects?

Biomedical Data Scientists often work closely with clinicians, biologists, and other researchers to translate complex biomedical questions into data-driven solutions. This collaboration usually involves regular meetings to understand clinical needs, define project goals, and discuss data interpretation. Effective communication is key, as team members may have different expertise and perspectives. By collaborating, Biomedical Data Scientists help ensure that analytical methods and results are both rigorous and clinically relevant, ultimately contributing to impactful healthcare outcomes.

What careers fall under biomedical science?

Careers under biomedical science include roles such as biomedical researcher, clinical scientist, laboratory technician, bioinformatics analyst, and medical scientist. These positions often require knowledge of biology, chemistry, data analysis, and proficiency with laboratory or computational tools.

What does a biomedical data scientist do?

A biomedical data scientist analyzes complex biological and medical data to identify patterns and insights that can improve healthcare and research. They use statistical methods, machine learning, and programming tools like Python or R to interpret data from sources such as genomics, clinical trials, and electronic health records. Their work supports diagnostics, treatment development, and personalized medicine efforts.

How much do biomedical data scientists make in the US?

Biomedical data scientists in the US typically earn a median salary of around $90,000 to $110,000 per year, depending on experience, education, and location. Advanced skills in programming, statistical analysis, and knowledge of biomedical data are often required and can lead to higher compensation.

Is biomedical data science a good career?

Biomedical data science is a growing field that combines data analysis, machine learning, and biology to improve healthcare and medical research. It offers high demand for skilled professionals with expertise in programming, statistics, and domain knowledge, often requiring advanced degrees. The career provides opportunities in research institutions, healthcare companies, and biotech firms with competitive salaries and ongoing innovation.

What are the key skills and qualifications needed to thrive as a Biomedical Data Scientist, and why are they important?

To thrive as a Biomedical Data Scientist, you need a strong background in statistics, machine learning, programming (typically Python or R), and a solid understanding of biological or clinical data. Familiarity with bioinformatics tools, data visualization platforms, high-throughput sequencing technologies, and relevant certifications (such as in data science or bioinformatics) is commonly required. Strong problem-solving abilities, communication skills, and interdisciplinary collaboration help set top professionals apart in this field. These competencies are crucial for extracting meaningful insights from complex biomedical data, driving research innovation, and supporting evidence-based healthcare decisions.
What cities in California are hiring for Biomedical Data Science jobs? Cities in California with the most Biomedical Data Science job openings:
Infographic showing various Biomedical Data Science job openings in California as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $108,894 per year, or $52.4 per hour.

$126K - $234K/yr

Full-time

Medical, Life, Retirement, PTO

Posted 3 days ago


Job description

Band

Level 4


Job Description Summary

Position Location: onsite, San Diego, CA
#LI-hybrid
*This role is based in San Diego, CA. Please only apply if this location is accessible for you.
The Oncology Data Science group within Biomedical Research supports the Oncology Disease Area with computational biology, Artificial Intelligence / Machine Learning (AI/ML), and data engineering for novel therapeutics across multiple drug modalities. As integrated scientists and engineers, we apply advanced analytics to pre-clinical and clinical projects, enabling progress in target discovery, drug development, and translational and clinical science.
Help us bring innovative drugs to the clinic by analyzing and interpreting multi-dimensional molecular data ('omics) into target identification, drug development, and patient biomarker discovery.
The Low Molecular Weight (LMW) team at Novartis Biomedical Research Oncology Data Science is seeking a highly motivated Senior Computational Scientist to join our team. With a focus on induced proximity therapeutics, you will collaborate with cross-functional teams in Biomedical Research and Oncology stakeholders to advance efforts in target identification and drug development to support our ground-breaking drug discovery programs.


Job Description

Major accountabilities:

  • Collaborate closely with interdisciplinary wet-lab and computational scientists to design, analyze, and interpret high-dimensional biological data (e.g., bulk RNA-seq, DNA-seq, CRISPR, drug screening) to inform critical project decision.

  • Lead profiling strategies and analysis of high-throughput genomic and phenotypic screening data to inform patient stratification and mechanism of resistance, in support of drug discovery and development.

  • Integrate multi-modal internal and external preclinical datasets (e.g., genomics, transcriptomics, pharmacology, and functional screens) to produce translationally relevant insights.
    Apply advanced bioinformatics and machine learning approaches across multi-modal datasets to uncover novel, actionable biological insights and therapeutic hypotheses.

  • Develop and implement innovative analytical methods to support emerging technologies and to effectively integrate, interrogate, and visualize multi-dimensional datasets.

  • Drive oncology research by leveraging data mining and genomic profiling to identify novel targets for induced proximity modality, elucidate mechanism of action and support patient stratification strategies.

  • Communicate integrative analyses and key findings clearly and effectively to diverse audiences, including cross-functional scientific teams and stakeholders.

Qualifications:

  • PhD in Computational Biology, System Biology, Bioinformatics, Data/Computer Science, or related field with relevant industry experience.

  • Strong knowledge of cancer biology and multi-modal data types such as genomics, transcriptomics, proteomics and phenotypic screening data.
    Proficiency in one or more programming languages for bioinformatics applications (e.g., Python, R) with experience in UNIX/Linux environment, version control, and reproducible workflows.
    Demonstrated statistical rigor and analytic depth in the analysis of high-dimensional omics datasets (e.g., bulk and single-cell transcriptomics, genomics).

  • Demonstrated experience leveraging AIassisted coding tools (e.g., copilots, code generators, and LLM-based workflows) to accelerate data analysis, model development, and reproducible scientific pipelines.

  • Familiarity with data workflows, including preclinical biomarker discovery and validation; survival analysis is a plus.

  • Proven ability to work independently, prioritize tasks effectively, define next steps and manage multiple projects and stakeholders in a fast-paced environment.

  • Excellent communication skills, with the ability to deliver complex scientific concepts to diverse audiences.
    Curiosity, creativity and a solution-oriented mindset when addressing scientific problems.
    Fluency in English (written and verbal).

The salary for this position is expected to range between $126,000 and $234,000 per year. The final salary offered is determined based on factors like, but not limited to, relevant skills andexperience, and upon joining Novartis will be reviewed periodically. Novartis may change the publishedsalary range based on company and market factors.
Your compensation will include a performance-based cash incentive and, depending on the level of therole, eligibility to be considered for annual equity awards.
US-based eligible employees will receive a comprehensive benefits package that includes health, life anddisability benefits, a 401(k) with company contribution and match, and a variety of other benefits. Inaddition, employees are eligible for a generous time off package including vacation, personal days,holidays and other leaves.


To learn more about the culture, rewards and benefits we offer our people clickhere.


EEO Statement:

The Novartis Group of Companies are Equal Opportunity Employers. We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, gender identity or expression, marital or veteran status, disability, or any other legally protected status. We strive to create an inclusive workplace that cultivates bold innovation through collaboration and empowers our people to unleash their full potential.


Accessibility and reasonable accommodations

The Novartis Group of Companies are committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application process, or in order to perform the essential functions of a position, please send an e-mail to tas.nacomms@novartis.com call +1 (877)395-2339 and let us know the nature of your request and your contact information. Please include the job requisition number in your message.
https://www.novartis.com/careers/careers-research/notice-all-applicants-us-job-openings


Salary Range

$126,000.00 - $234,000.00


Skills Desired

Artificial Intelligence (AI), Biostatistics, Change Management, Curious Mindset, Data Governance, Data Literacy, Data Quality, Data Science, Data Visualization, Deep Learning, Graph Algorithms, Learning Agility, Logistic Regression Model, Machine Learning (ML), Machine Learning Algorithms, Nlp (Neuro-Linguistic Programming) And Genai, Pandas (Python), Python (Programming Language), R (Programming Language), Sql (Structured Query Language), Stakeholder Engagement, Statistical Analysis, Time Series Analysis