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Healthcare Data Science Jobs in California (NOW HIRING)

Astiva Health

Healthcare Data Analyst

Orange, CA

$85K - $115K/yr

Bachelor's degree in Data Analytics, Health Informatics, Statistics, Computer Science, or related field. * 2-5+ years of healthcare data analytics experience. * Knowledge of Medicare Advantage ...

Astiva Health

Healthcare Data Analyst

Orange, CA · On-site

$85K - $115K/yr

Bachelor's degree in Data Analytics, Health Informatics, Statistics, Computer Science, or related field. * 2-5+ years of healthcare data analytics experience. * Knowledge of Medicare Advantage ...

Latica AI

Senior Data Scientist

Palo Alto, CA · On-site

$160K - $190K/yr

Latica was founded by repeat entrepreneurs and recognized leaders in healthcare, data science, AI, and cybersecurity. We look for people who are smart, open, and enjoyable to work with. We invest in ...

Latica

Senior Data Scientist

Palo Alto, CA · On-site

$160K - $190K/yr

Latica was founded by repeat entrepreneurs and recognized leaders in healthcare, data science, AI, and cybersecurity. We look for people who are smart, open, and enjoyable to work with. We invest in ...

Latica

Senior Data Scientist

Palo Alto, CA

$160K - $190K/yr

Latica was founded by repeat entrepreneurs and recognized leaders in healthcare, data science, AI, and cybersecurity. We look for people who are smart, open, and enjoyable to work with. We invest in ...

Onos

Lead Data Scientist

San Francisco, CA · On-site

$200K - $225K/yr

What we're looking for: * 8+ years of experience in data science or advanced analytics (preferably in healthcare or health plans; experience with claims and clinical data strongly preferred). * Deep ...

Pwc

Payer Healthcare Data Scientist, Manager

San Diego, CA · On-site

$99K - $232K/yr

The Opportunity As part of the Operations Consulting team, you will apply advanced data science and ... care and improve population health outcomes for our payer clients. As a Manager, you will lead ...

Heluna Health

Data Scientist Supervisor

Alhambra, CA · On-site

$9.8K - $13K/mo

... healthcare data to support decision-making across the Los Angeles County Department of Health ... Quality Assurance & Best Practices - Establish and enforce best practices in data science ...

Heluna Health

Data Scientist Supervisor

Alhambra, CA · On-site

$9.8K - $13K/mo

... healthcare data to support decision-making across the Los Angeles County Department of Health ... Quality Assurance & Best Practices - Establish and enforce best practices in data science ...

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All JobsHealthcare Data Science JobsHealthcare Data Science Jobs in California

Healthcare Data Science information

See California salary details

$45.4K

$162.9K

$240.3K

How much do healthcare data science jobs pay per year?

As of Aug 6, 2026, the average yearly pay for healthcare data science in California is $162,857.00, according to ZipRecruiter salary data. Most workers in this role earn between $131,800.00 and $167,800.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a healthcare data scientist?

To thrive as a Healthcare Data Scientist, you need a strong background in statistics, data analysis, programming (Python or R), and an understanding of healthcare systems, often supported by a degree in data science, computer science, or a related field. Experience with tools like SQL, machine learning frameworks, and familiarity with electronic health record (EHR) systems are typically required. Strong problem-solving skills, attention to detail, and effective communication help translate complex data insights into actionable healthcare solutions. These skills are crucial for deriving meaningful insights from complex healthcare data, improving patient outcomes, and supporting evidence-based decision-making.

What is the difference between Healthcare Data Science vs Healthcare Data Analysis?

AspectHealthcare Data ScienceHealthcare Data Analysis
Required CredentialsTypically requires a degree in data science, statistics, or related fields; often includes programming skills and knowledge of machine learningUsually requires a background in healthcare, statistics, or data analysis; may include certifications in data analysis tools
Work EnvironmentInvolves developing models, algorithms, and predictive analytics; often in research or tech-focused settingsFocuses on interpreting data, generating reports, and supporting clinical or administrative decisions
Employer & Industry UsageUsed by healthcare tech companies, research institutions, and large healthcare providersCommon in hospitals, clinics, insurance companies, and healthcare consulting firms

Healthcare Data Science and Healthcare Data Analysis share overlapping skills but differ mainly in scope. Data scientists develop advanced models and predictive tools, while data analysts focus on interpreting data and generating insights. Both roles are vital in healthcare but serve different functions within the industry.

What are some common challenges faced by healthcare data scientists when working with clinical data?

Healthcare data scientists often navigate challenges such as dealing with incomplete or inconsistent medical records, ensuring patient privacy and data security, and integrating data from diverse sources like electronic health records, lab results, and imaging systems. Additionally, they must collaborate closely with clinicians and IT staff to interpret complex datasets accurately and ensure that their analyses have practical clinical value. Maintaining compliance with healthcare regulations, such as HIPAA, is also a critical aspect of the role.

What can you do with a degree in healthcare data science?

A degree in healthcare data science prepares individuals to analyze medical data, develop predictive models, and improve patient outcomes. Graduates can work as data analysts, data scientists, or informaticists in hospitals, healthcare companies, or research institutions, often using tools like Python, R, and SQL. The role involves interpreting complex data to support clinical decisions and healthcare policies.

What is healthcare data science?

Healthcare data science is a field that uses data analysis, statistics, and machine learning to extract insights from health-related data. Professionals in this area work with large datasets from sources like electronic health records, clinical trials, and wearable devices. Their goal is to improve patient outcomes, optimize hospital operations, and support medical research by turning raw data into actionable information. This field requires knowledge of healthcare systems, data management, and advanced analytics techniques.

Can a healthcare data scientist work in healthcare?

Yes, healthcare data scientists work within healthcare organizations to analyze medical data, improve patient outcomes, and optimize operational efficiency. They often use tools like Python, R, and SQL, and require knowledge of healthcare systems, data privacy regulations, and statistical methods.
What are the most commonly searched types of Healthcare Data Science jobs in California? The most popular types of Healthcare Data Science jobs in California are:
What are popular job titles related to Healthcare Data Science jobs in California? For Healthcare Data Science jobs in California, the most frequently searched job titles are:
What job categories do people searching Healthcare Data Science jobs in California look for? The top searched job categories for Healthcare Data Science jobs in California are:
What cities in California are hiring for Healthcare Data Science jobs? Cities in California with the most Healthcare Data Science job openings:
Healthcare Data Science jobs near you
Infographic showing various Healthcare Data Science job openings in California as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 21% Part Time, 2% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $162,857 per year, or $78.3 per hour.

Healthcare Data Scientist (RWD)

Medeloop

San Francisco, CA

Other

Posted 5 days ago

Job description

We are seeking a Healthcare Data Scientist (Real-World Evidence) to answer complex healthcare and biopharma questions using large-scale real-world data and help shape the next generation of AI-powered clinical research. This is a hands-on role that combines rigorous real-world evidence analysis with deep collaboration across product, AI, and customer teams.

Internally, you will partner closely with Medeloop's AI research and product teams to design and execute real-world evidence analyses, evaluate the performance of our clinical research agents, and apply your scientific expertise to improve how our platform reasons about healthcare data. Externally, you will serve as an embedded data scientist for our partner institutions, working directly with clinicians, researchers, and life sciences organizations to scope research questions, deliver high-quality evidence, drive adoption of the platform, and expand each customer's use of Medeloop over time. This is a highly technical role centered on analytical reasoning, statistical rigor, and scientific problem-solving. Your work will directly influence both the intelligence of our AI systems and the real-world impact they create for healthcare and life sciences organizations.

Role & Responsibilities

  • Build and execute real-world evidence analyses to answer complex healthcare and biopharma questions using large-scale claims and EHR data.
  • Write high-quality, scalable code (SQL and Python; R also welcome) to define cohorts, model patient journeys, and generate rigorous, reproducible research outputs.
  • Apply clinical and statistical judgment to evaluate treatment patterns, utilization, and outcomes in observational data, reasoning carefully about bias and limitations.
  • Work directly with Medeloop's AI research agents, reviewing and challenging their analytical outputs, and partner with AI and product teams to improve how agents translate research questions into high-quality analyses.
  • Partner with customer institutions: scope their research questions, deliver evidence, drive adoption, and help expand how each institution uses Medeloop.
  • Communicate analyses, assumptions, and limitations clearly to internal teams, scientific stakeholders, and customers, translating technical findings into plain-language insight.
  • Help shape the analytical foundations and evaluation frameworks behind the next generation of AI-driven clinical research tools.
Requirements
  • PhD, or a Master's degree minimum plus 5+ years of industry experience, in a quantitative-health field (biostatistics, epidemiology, clinical trials, public health, health informatics, or health economics). PhD preferred; strong industry experience can substitute for the doctorate.
  • Strong grounding in real-world data/evidence (RWD/RWE) methodology, with domain experience in biostatistics, epidemiology, clinical trials, or public health.
  • Proven ability to answer complex clinical or biopharma questions using SQL and Python, plus statistical software (R and/or SAS).
  • Experience with large healthcare datasets, such as claims or EHR data (clinical coding systems, ICD/CPT/RxNorm), assumed to come with an RWE background.
  • Track record of producing rigorous, research-grade analyses, reports, or publications; comfort working with messy, high-dimensional data.
  • AI/ML experience required, with clear evidence of hands-on use; comfortable reviewing code and reasoning about model outputs.
  • Strong communicator; customer-facing experience preferred (trainable for the right analytical candidate).
Nice to Have
  • Experience working directly with customers and in a sales capacity.
  • Industry background strongly preferred over consulting (industry candidates preferred over consultants).

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