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Senior Healthcare Data Scientist Jobs (NOW HIRING)

Latica AI

Senior Data Scientist

Palo Alto, CA · On-site

$160K - $190K/yr

Who We Are At Latica, our goal is to unlock the value of healthcare data to transform patient care ... Latica was founded by repeat entrepreneurs and recognized leaders in healthcare, data science, AI ...

Latica

Senior Data Scientist

Palo Alto, CA · On-site

$160K - $190K/yr

Who We Are At Latica, our goal is to unlock the value of healthcare data to transform patient care ... Latica was founded by repeat entrepreneurs and recognized leaders in healthcare, data science, AI ...

Spectrum Health

Data Scientist Senior

Grand Rapids, MI · On-site +1

Job Summary The Senior Data Scientist is responsible for leading data science projects and ... At least 5 years of relevant experience in a quantitative discipline health care, data science ...

Pwc

Payer Healthcare Data Scientist, Manager

Phoenix, AZ · On-site

$99K - $232K/yr

... impact in healthcare. Responsibilities - Apply advanced data science and machine learning ... senior stakeholders, including Chief Actuaries - Play a key role in the development of new ...

Pwc

Payer Healthcare Data Scientist, Manager

Melville, NY · On-site

$99K - $232K/yr

... impact in healthcare. Responsibilities - Apply advanced data science and machine learning ... senior stakeholders, including Chief Actuaries - Play a key role in the development of new ...

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Senior Healthcare Data Scientist information

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$41.5K

$142.5K

$201K

How much do senior healthcare data scientist jobs pay per year?

As of Aug 8, 2026, the average yearly pay for senior healthcare data scientist in the United States is $142,460.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,500.00 and $166,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a senior healthcare data scientist, and why are they important?

To thrive as a Senior Healthcare Data Scientist, you need advanced expertise in statistics, machine learning, and healthcare analytics, typically supported by a graduate degree in a quantitative field. Proficiency with programming languages like Python or R, data visualization tools, and experience with healthcare data systems (such as EHRs or claims databases) are standard requirements. Strong communication, problem-solving, and leadership skills help you translate complex data insights for clinical and executive audiences. These skills are essential for driving data-driven decision-making and innovation in the rapidly evolving healthcare sector.

What is the difference between Senior Healthcare Data Scientist vs Healthcare Data Analyst?

AspectSenior Healthcare Data ScientistHealthcare Data Analyst
Required CredentialsAdvanced degrees (Master's/PhD), data science certificationsBachelor's or Master's in health informatics, data analysis
Work EnvironmentResearch labs, healthcare organizations, tech companiesHospitals, clinics, healthcare providers, insurance companies
Employer & Industry UsageUsed for developing predictive models, advanced analyticsFocuses on data reporting, basic analysis, and visualization

The main difference between a Senior Healthcare Data Scientist and a Healthcare Data Analyst lies in their roles and expertise. Senior Healthcare Data Scientists typically handle complex modeling, machine learning, and predictive analytics, requiring advanced credentials. Healthcare Data Analysts focus on data reporting, visualization, and basic analysis to support decision-making. Both roles are vital in healthcare but differ in complexity and scope.

How does a senior healthcare data scientist typically collaborate with clinical and IT teams to drive data-driven decision making?

A Senior Healthcare Data Scientist frequently works cross-functionally with clinical and IT teams to translate complex healthcare data into actionable insights. This involves gathering requirements from clinicians, ensuring data integrity with IT professionals, and presenting analytical findings in a way that is accessible to non-technical stakeholders. Effective communication and a collaborative approach are essential, as data scientists often help bridge the gap between technical capabilities and clinical needs. These collaborations not only improve patient outcomes but also streamline healthcare operations.

What is a senior healthcare data scientist?

Senior Healthcare Data Scientists are experienced professionals who analyze complex health-related data to improve patient outcomes, optimize healthcare operations, and support decision-making within medical organizations. They use advanced analytics, machine learning, and statistical techniques to uncover patterns from large datasets, such as electronic health records and medical claims. Their responsibilities often include leading data projects, collaborating with clinicians and IT teams, and ensuring data quality and privacy. With their expertise, they help healthcare organizations implement evidence-based strategies and innovative solutions to enhance patient care and operational efficiency.
What cities are hiring for Senior Healthcare Data Scientist jobs? Cities with the most Senior Healthcare Data Scientist job openings:
What are the most commonly searched types of Healthcare Data Scientist jobs? The most popular types of Healthcare Data Scientist jobs are:
What states have the most Senior Healthcare Data Scientist jobs? States with the most job openings for Senior Healthcare Data Scientist jobs include:
Senior Healthcare Data Scientist jobs near you
Infographic showing various Senior Healthcare Data Scientist job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $142,460 per year, or $68.5 per hour.

Healthcare Data Scientist (RWD)

Medeloop

San Francisco, CA

Full-time

Posted 7 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).