ZipRecruiter

Log In

1

Internship Healthcare Data Science Jobs in California

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 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 ...

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

$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 ...

Onos

Lead Data Scientist

San Francisco, CA · On-site

$200K - $225K/yr

What We're Looking For * 8+ years of experience in healthcare analytics, data science, biostatistics, or a related quantitative field. * Deep experience working with healthcare claims, clinical ...

Knit Health

Senior Data Scientist

San Francisco, CA · On-site

$140K - $175K/yr

... healthcare organizations can use. As a senior member of a small data science team, this person will also help establish strong scientific and analytical practices while supporting the growth of ...

next page

Showing results 1-20

All JobsHealthcare Data Science JobsInternship Healthcare Data Science JobsInternship Healthcare Data Science Jobs in California

Internship Healthcare Data Science information

What is an internship in healthcare data science?

An internship in healthcare data science is a temporary position, often for students or recent graduates, that provides hands-on experience in analyzing and interpreting healthcare data. Interns typically work with professionals on projects involving data cleaning, statistical analysis, machine learning, and data visualization to support healthcare decision-making and improve patient outcomes. These internships help participants develop technical skills, gain industry knowledge, and build professional networks in the rapidly growing field of healthcare data science.

What are the key skills and qualifications needed to thrive as an internship in healthcare data science?

To thrive as an intern in healthcare data science, you need a solid grasp of statistics, data analysis, and programming languages such as Python or R, typically supported by coursework or a degree in data science, computer science, or a related field. Familiarity with data visualization tools (e.g., Tableau), healthcare databases (e.g., EHR systems), and knowledge of HIPAA regulations are often expected. Strong problem-solving skills, attention to detail, and effective communication make candidates stand out in this role. These capabilities are essential for transforming complex healthcare data into actionable insights that improve patient outcomes and support data-driven decision-making.

What types of projects do interns in healthcare data science typically work on, and how do these projects contribute to real-world healthcare improvements?

Interns in Healthcare Data Science often work on projects such as analyzing patient data to identify trends, developing predictive models for disease progression, or optimizing hospital resource allocation. These projects are usually part of larger, cross-functional teams including clinicians, IT specialists, and senior data scientists. The outcomes of your work can directly impact patient care processes, inform decision-making, and improve operational efficiency in healthcare settings. Expect regular mentorship and feedback, as well as opportunities to present your findings to technical and non-technical stakeholders.

What is the difference between Internship Healthcare Data Science vs Healthcare Data Analyst?

AspectInternship Healthcare Data ScienceHealthcare Data Analyst
Required CredentialsTypically pursuing or recent graduate in data science, statistics, or related fieldOften requires degree in health informatics, statistics, or related field
Work EnvironmentInternship setting, often in hospitals, healthcare tech companies, or research institutionsFull-time or part-time roles in healthcare organizations, clinics, or health IT firms
Employer & Industry UsageUsed by healthcare providers, research institutions, and tech companies for training and entry-level rolesCommon in hospitals, insurance companies, and healthcare consulting firms for data analysis tasks

Internship Healthcare Data Science positions are entry-level, focused on training and gaining experience in data science techniques applied to healthcare. Healthcare Data Analysts are more established roles, responsible for analyzing healthcare data to support decision-making. Both roles require similar educational backgrounds but differ in experience level and job responsibilities.

Can data science be used in healthcare?

Healthcare Data Science is a field that applies data analysis, machine learning, and statistical methods to improve patient outcomes, optimize operations, and support clinical decision-making. Data scientists in healthcare often work with electronic health records, medical imaging, and health-related datasets using tools like Python, R, and SQL. This role requires understanding healthcare regulations and data privacy standards such as HIPAA.

How do I become a healthcare data scientist?

To become a healthcare data scientist, you typically need a strong background in data science, statistics, or computer science, often with a relevant bachelor's or master's degree. Skills in programming languages like Python or R, knowledge of healthcare data systems, and experience with data analysis tools are essential; certifications in data science or healthcare analytics can also enhance your qualifications.

How to get an internship in healthcare data science?

To secure a healthcare data science internship, candidates should have a strong foundation in data analysis, programming (such as Python or R), and knowledge of healthcare systems. Relevant coursework, certifications in data science or healthcare analytics, and experience with tools like SQL and machine learning can improve chances. Applying through university career services, networking with industry professionals, and demonstrating project work are also effective strategies.

What are popular job titles related to Internship Healthcare Data Science jobs in California?

For Internship Healthcare Data Science jobs in California, the most frequently searched job titles are:

What job categories do people searching Internship Healthcare Data Science jobs in California look for?

The top searched job categories for Internship Healthcare Data Science jobs in California are:

What cities in California are hiring for Internship Healthcare Data Science jobs?

Cities in California with the most Internship Healthcare Data Science job openings:

Internship Healthcare Data Science jobs near you
Infographic showing various Internship Healthcare Data Science job openings in California as of August 2026, with employment types broken down into 100% Part Time. Highlights an 100% In-person job distribution.

Healthcare Data Scientist (RWD)

Medeloop

San Francisco, CA • On-site

Full-time

Re-posted 3 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).

Apply