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Biomedical Data Science Jobs in California (NOW HIRING)

AstraZeneca

Data Scientist

Santa Monica, CA · On-site

Lead bioinformatic and data science efforts focused on singlecell RNAseq (scRNAseq) data, including ... Solid understanding of statistical methods and their application to singlecell and biomedical data.

AstraZeneca

Data Scientist

Santa Monica, CA · On-site

Key Responsibilities Lead bioinformatic and data science efforts focused on singlecell RNAseq ... Solid understanding of statistical methods and their application to singlecell and biomedical data.

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All JobsBiomedical Data Science JobsBiomedical Data Science Jobs in California

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 are popular job titles related to Biomedical Data Science jobs in California? For Biomedical Data Science jobs in California, the most frequently searched job titles are:
What job categories do people searching Biomedical Data Science jobs in California look for? The top searched job categories for Biomedical Data Science jobs in California are:
What cities in California are hiring for Biomedical Data Science jobs? Cities in California with the most Biomedical Data Science job openings:
Biomedical Data Science jobs near you
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.
Biomedical Data Science Engineer - Health Technologies

Biomedical Data Science Engineer - Health Technologies

Apple

San Diego, CA • On-site

$59.25 - $78.25/hr

Full-time

Posted 28 days ago

Apple rating

8.1

Company rating: 8.1 out of 10

Based on 661 frontline employees who took The Breakroom Quiz

6th of 30 rated technology retailers

Job description

The Health Technologies Team conceives and proves out exciting new technology for Apple's future products and features. In this role, you can be involved in the end-to-end new product development cycle for health and wellness technologies, from product ideation and feasibility assessment to algorithm implementation and product validation. Join our team to create extraordinary features that represent the cutting edge of innovation in the dynamic consumer health field.
In this role, you'll collaborate with multidisciplinary teams to create innovative health products and features. As a biomedical data scientist, your responsibilities will include: -design and support of lab and human studies ranging from small scale pilot investigations to large scale sensor fusion studies -distill and interpret study findings to assess system performance and confounders -define and evaluate sensor feasibility criteria, including KPI development, mapping user experience requirements to sensor specifications -develop analysis tools to evaluate and interpret physiological time series sensor data -design, implement, and validate physiological models and algorithms -develop data visualization strategies for sharing complex data and study findings to influence project decisions and direction. The role requires effective collaboration with team members spanning a broad range of expertise and disciplines. Flexible thinking, adaptability to change, comfort with ambiguity, and ability to work both independently as well as in a team setting are hallmarks of success on our team.
MS in Biomedical engineering or other engineering discipline with relevant prior experience with time-series physiological sensors, devices, and applications.Must have a strong understanding of human physiology coupled with experience in the use of multi-sensor systems to measure, characterize, and analyze time-series physiological signals.Must have experience using Python to process, analyze, and visualize data. Must be facile with the corresponding Python tools (e.g., matplotlib, plotly, tableau, etc.).Must be highly organized and able to thrive in a fast-paced environment. Must have excellent communication skills.
PhD in Biomedical engineering or other engineering discipline with relevant prior experience.Experience with deep learning frameworks (e.g., PyTorch) including model training, loss function design, optimization, and cross-validation.Experience with statistical testing methods and their application to experimental data analysis.Experience with distributed processing frameworks (e.g., Spark, Dask) for large-scale data workflows.Experience with data management, organization, storage, and retrieval.

What Apple employees say

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Benefits

Hours and flexibility

Workplace

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976

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