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Full Time Healthcare Data Analytics Jobs (NOW HIRING)

Medeloop

Healthcare Data Scientist (RWD)

Boston, MA · On-site

This is a hands-on role that combines rigorous real-world evidence analysis with deep collaboration ... healthcare data. Externally, you will serve as an embedded data scientist for our partner ...

HART, INC.

Healthcare Data Engineer, Team Lead

Kansas City, MO · On-site

$111K - $134K/yr

S., helping them simplify EHR data migrations, archival, interoperability, and analytics through its suite of innovative products and professional services. Hart's mission is to make healthcare data ...

New

Chapa-De

Leader of Data and Analytics

Auburn, CA · On-site

$118K - $140K/yr

... healthcare data, analytics, or informatics roles in lieu of a degree. * 3-5 years progressively ... responsible experience in healthcare data management, analytics or reporting. * Minimum 2 years of ...

Bellin

Accountable Care Data Analyst

Green Bay, WI · On-site

... Full-Time 1.00 FTE (40 hours/week) Work Schedule: Monday - Friday. Days Want to learn more: Chat ... a healthcare setting; with emphasis care transformation, analytics, and Value Based Care ...

Collabrios Health

SVP, Data Sales

Job Type Full-time Description Collabrios delivers purpose-built software solutions that unify the ... for healthcare data and analytics offerings. * Identify, qualify, and close new business ...

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How much do full time healthcare data analytics jobs pay per hour?

As of Aug 20, 2026, the average hourly pay for full time healthcare data analytics in the United States is $54.75, according to ZipRecruiter salary data. Most workers in this role earn between $43.99 and $62.02 per hour, depending on experience, location, and employer.

How to get a job in full time healthcare data analytics?

To secure a full-time healthcare data analytics position, candidates should have a strong foundation in data analysis, statistics, and healthcare systems, often supported by a degree in health informatics, data science, or related fields. Proficiency in tools like SQL, Python, or R, along with knowledge of electronic health records and healthcare regulations, is essential. Gaining relevant experience through internships or certifications such as Certified Health Data Analyst (CHDA) can improve job prospects.

Is full time healthcare data analytics a good career?

Full time healthcare data analytics is a growing field that offers opportunities to improve patient outcomes and healthcare operations through data analysis, often requiring skills in statistical tools, programming, and understanding healthcare systems. It provides stable employment with increasing demand due to the expansion of electronic health records and data-driven decision making. However, success typically depends on relevant education, certifications, and staying current with industry technologies.

What cities are hiring for Full Time Healthcare Data Analytics jobs?

Cities with the most Full Time Healthcare Data Analytics job openings:

What are the most commonly searched types of Healthcare Data Analytics jobs?

The most popular types of Healthcare Data Analytics jobs are:

What states have the most Full Time Healthcare Data Analytics jobs?

States with the most job openings for Full Time Healthcare Data Analytics jobs include:

Full Time Healthcare Data Analytics jobs near you
Infographic showing various Full Time Healthcare Data Analytics job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $113,873 per year, or $54.7 per hour.

Healthcare Data Scientist (RWD)

Medeloop

Philadelphia, PA • On-site

Full-time

Posted 19 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).