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Senior Healthcare Data Science Jobs (NOW HIRING)

Experience preparing and analyzing large healthcare data sets, such as claims, electronic health ... Tools for data science : Familiarity with modern coding standards for data science including ...

Experience preparing and analyzing large healthcare data sets, such as claims, electronic health ... Tools for data science : Familiarity with modern coding standards for data science including ...

Stay current on the latest advancements in healthcare data science and machine learning. Qualifications: Minimum 5 years of experience in data science or a related field. Less ok too, if they have a ...

The Healthcare Data Analyst partners closely with Finance, IT, Quality, Clinical Operations, and Senior Leadership to strengthen reporting, identify opportunities, and support initiatives across ...

At Counterpart Health, we are transforming healthcare and improving patient care with our ... The Data Science team is responsible for leveraging our most valuable asset-our data-to generate ...

$60.70K - $61.20K/yr

Stay current with advancements in data science, statistical methods, and analytical tools relevant to healthcare operations. 12. Must pass Electronic medical record system Proficiency or ...

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Senior Healthcare Data Science information

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How much do senior healthcare data science jobs pay per hour?

As of May 31, 2026, the average hourly pay for senior healthcare data science in the United States is $56.81, according to ZipRecruiter salary data. Most workers in this role earn between $46.63 and $67.31 per hour, 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 master's or PhD in a quantitative field. Mastery of tools like Python, R, SQL, and familiarity with healthcare data standards and cloud platforms is essential. Strong problem-solving, communication, and leadership skills help drive impactful solutions and bridge the gap between technical teams and healthcare stakeholders. These abilities are critical for generating actionable insights, improving patient outcomes, and ensuring data-driven decision-making in complex healthcare environments.

What are some common challenges faced by Senior Healthcare Data Scientists when working with clinical data?

Senior Healthcare Data Scientists often navigate challenges such as integrating data from diverse sources, ensuring data quality, and maintaining patient privacy in compliance with regulations like HIPAA. Dealing with incomplete or inconsistent electronic health records can be time-consuming, requiring strong data cleaning and validation skills. Collaboration with clinicians and IT teams is essential to accurately interpret data and translate findings into actionable insights for patient care and strategic decision-making.

What is a Senior Healthcare Data Scientist?

A Senior Healthcare Data Scientist is an experienced professional who analyzes complex health-related data to improve patient outcomes, healthcare operations, and decision-making. They use advanced statistical methods, machine learning, and data modeling to interpret medical records, clinical trial results, insurance claims, and other healthcare data sources. In addition to technical expertise, they often collaborate with clinicians, administrators, and IT teams to implement data-driven solutions and support evidence-based practices. Their work helps healthcare organizations optimize care delivery, reduce costs, and advance medical research.

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

AspectSenior Healthcare Data ScienceHealthcare Data Analyst
Required CredentialsAdvanced degrees (Master's/PhD), experience in data science, programming skillsBachelor's degree, proficiency in data analysis tools, basic statistical knowledge
Work EnvironmentCross-functional teams, research projects, predictive modelingData reporting, data cleaning, basic analysis in healthcare settings
Employer & Industry UsageHospitals, healthcare tech companies, research institutionsClinics, insurance companies, healthcare providers
Common Search & Comparison IntentUnderstanding senior-level roles, qualifications, responsibilitiesEntry to mid-level analysis tasks, data reporting roles

Senior Healthcare Data Scientists focus on advanced analytics, predictive modeling, and developing algorithms, often requiring higher education and specialized skills. Healthcare Data Analysts perform routine data reporting and basic analysis. While both roles work within healthcare, they differ in complexity, responsibilities, and required expertise.

More about Senior Healthcare Data Science jobs
What cities are hiring for Senior Healthcare Data Science jobs? Cities with the most Senior Healthcare Data Science job openings:
What are the most commonly searched types of Healthcare Data Science jobs? The most popular types of Healthcare Data Science jobs are:
What states have the most Senior Healthcare Data Science jobs? States with the most job openings for Senior Healthcare Data Science jobs include:
Infographic showing various Senior Healthcare Data Science job openings in the United States as of May 2026, with employment types broken down into 1% Locum Tenens, 78% Full Time, 16% Part Time, and 5% Contract. Highlights an 86% Physical, 6% Hybrid, and 8% Remote job distribution, with an average salary of $118,171 per year, or $56.8 per hour.

Sr. Data Scientist, Clinical

Prolaio

Chicago, IL

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 5 days ago


Job description

Who Are We?

Prolaio believes that continuous learning and collaboration can make a significant difference in how heart care is administered. We are creating smarter ways to address heart disease and heart risks by uniting patients, care teams, and researchers on a secure, technology-enabled platform that drives clinical innovation and offers a path towards better patient outcomes.

This is precision cardiology, and we know it's within reach.

What Will You Do?

The Overview

The Senior Data Scientist, Clinical will leverage advanced data science methodologies to advance the science and clinical applications of digital biomarkers. This role involves developing rigorous technical plans and executing complex analyses on multimodal datasets (digital biomarkers from wearable data, electronic health records [EHR], claims) for publication in high-impact medical journals. The successful candidate will build pipelines to prepare analytic datasets from wearable data and EHR and utilize Python and/or R to develop multimodal risk prediction models to describe, predict, and estimate clinical effects.

The Specifics

  • Clinical Analysis & Publication: Design and execute statistical analyses on large clinical datasets. Author abstracts, statistical analysis plans, conference presentations, and manuscripts for publication in peer-reviewed medical journals.
  • Data Pipeline Development:  Build, document, and maintain reproducible data pipelines to curate analytic datasets, combining data from multiple assets (e.g., continuous signal data, claims, electronic health records, etc.).
  • Risk Prediction Modeling: Develop and deploy time-varying and multimodal risk prediction models which extract insights from contextual health data and physiologic signals
  • Scientific Leadership: Contribute to rigorous science that expands our understanding of digital biomarkers and clinical endpoints in cardiovascular disease in order to enable Prolaio's ability to support clinical research and cardiovascular care.
  • Cross-Functional Collaboration: Collaborate cross-functionally with data engineering, operations, clinical, and other teams to ensure data analyses and modeling pipelines align with cross-team standards, scientific validity and company objectives.
  • Advanced Data Abstraction: Utilize both traditional programmatic and (where applicable) modern LLM-based techniques for complex data processing and clinical abstraction.

Why Prolaio?

  • Impactful Work: You will join in the fight against heart failure (HF) and hypertrophic cardiomyopathy (HCM) with the goal of extending and saving the lives of our patients while also being at the forefront of changing the healthcare industry through technology.
  • Innovative Environment: You will be part of an organization doing something that's never been done before.
  • Professional Growth: You will join a growing team and have a substantial impact on our daily and future operations with the opportunity to continuously learn and grow.
  • Collaborative Team: You will be part of a team of collaborative, curious, and committed individuals focused on the collective good, inclusiveness, scientific excellence, and advancing digital health for cardiology.

Who You Are?

  • Education & Experience: PhD, MD, or master's degree. 3+ years of academic or industry experience post-PhD/MD or 5+ years post-master's in any of the following fields: applied statistics, biostatistics, epidemiology, health economics, data science, health informatics, or a related field.
  • Scientific Track Record: A strong track record of peer-reviewed scientific publications, with experience communicating scientific results through presentations, abstracts, and manuscripts.
  • Healthcare Data Expertise: Experience preparing and analyzing large healthcare data sets, such as claims, electronic health records, or clinical trials. Experience with the specification of clinical event definitions and familiarity with healthcare data standards/ontologies (e.g., FHIR, OMOP, ICD-10, CPT).
  • Time-Series Data: Experience processing and analyzing high-volume time-series data.
  • Technical Proficiency: Experience in Python for machine learning and pipeline development. Experience in R for biostatistical inference is a plus.
  • Core Expertise: Deep expertise in at least TWO or more of the following three areas: 
    • Agentic LLMs: Experience designing and validating LLM-based agentic pipelines (e.g., with LangChain, Vertex AI, etc.). Experience fine-tuning LLMs is a plus.
    • Machine learning for multimodal data: Completed projects in Python to develop predictive health risk models using common data sciences libraries (e.g., scikit-learn, etc.) and completed projects utilizing deep learning frameworks (e.g., PyTorch, Jax) for time-series, computer vision, or multimodal data.
    • Biostatistics & Epidemiology: Proven ability to implement models for statistical inference, with specific expertise in longitudinal health data, time-to-event (survival) analysis, and disease trajectories. Deep understanding of epidemiologic concepts (bias, confounding, data missingness) and familiarity with study design for observational studies and randomized controlled trials.
  • Tools for data science: Familiarity with modern coding standards for data science including reproducible environment management  (e.g. poetry, uv, renv), version control (Git), robust documentation, report generation (e.g. Quarto), and SQL. Experience with production tools for continuous integration, deployment, and experiment tracking (e.g. MLflow and metaflow)
  • Communication: Ability to work cross-functionally and seamlessly translate highly technical concepts to non-technical audiences and stakeholders.

Additional Qualifications (Nice to Haves)

  • Prior research or industry experience in cardiovascular disease (CVD) or digital cardiology.
  • Prior experience with data from wearables or other sensor data.

Why You'll Love Working Here

  • Meaningful Compensation: Competitive salary, performance bonus, and equity so you can share in what we build.
  • Great Health Coverage: Medical, dental, and vision plans with multiple options and strong company contributions.
  • Flexible Spending Perks: HSA, FSA, commuter benefits, and a $1,200 annual Lifestyle Spending Account to support wellness, commuting, family needs, and more.
  • Time to Recharge: Generous paid time off, sick leave, and company holidays.
  • Family-First Benefits: Paid parental leave, caregiver leave, and support for growing families.
  • Security & Peace of Mind: Company-paid life insurance and short- and long-term disability coverage.
  • Plan for the Future: 401(k) plan to help you build long-term financial security.
  • Care When You Need It: Easy access to telehealth and optional supplemental coverage for life's unexpected moments.

Starting Salary is at $136,000.00 (Exact Compensation may vary based on skills, experience, and location)