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Cardiology Data Scientist Jobs (NOW HIRING)

Prolaio

Sr. Data Scientist, Clinical

Chicago, IL · On-site

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 ...

Prolaio

Sr. Data Scientist, Clinical

Chicago, IL

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 ...

Medpace, Inc.

AI Scientist

Cincinnati, OH

Do you have a background in data science and/or computer science with experience working with AI ... cardiology, metabolic disease, endocrinology, central nervous system, anti-viral and anti-infective.

Medpace, Inc.

AI Scientist

Cincinnati, OH · On-site

Do you have a background in data science and/or computer science with experience working with AI ... cardiology, metabolic disease, endocrinology, central nervous system, anti-viral and anti-infective.

Cleerly, LLC

Sr. ML Scientist

Boston, MA · On-site +1

We were founded in 2017 by one of the world's leading cardiologists and are a growing team of world ... In this role, you will collaborate with ML scientists, data engineers, biostatisticians, regulatory ...

Cleerly

Sr. ML Scientist

Boston, MA · On-site

We were founded in 2017 by one of the world's leading cardiologists and are a growing team of world ... In this role, you will collaborate with ML scientists, data engineers, biostatisticians, regulatory ...

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All JobsCardiology Data Scientist Jobs

Cardiology Data Scientist information

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$37.5K

$122.7K

$196.5K

How much do cardiology data scientist jobs pay per year?

As of Jun 8, 2026, the average yearly pay for cardiology data scientist in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What are Cardiology Data Scientists?

Cardiology Data Scientists are professionals who use data analysis, machine learning, and statistical tools to interpret complex cardiovascular data. They collaborate with cardiologists and medical researchers to analyze patient records, imaging data, and clinical trial results, aiming to improve diagnosis, treatment, and patient outcomes in cardiology. Their work often involves building predictive models, identifying trends, and translating large datasets into actionable insights for healthcare providers.

How does a Cardiology Data Scientist typically collaborate with clinicians and other healthcare professionals?

Cardiology Data Scientists work closely with cardiologists, nurses, and healthcare administrators to understand clinical challenges and translate them into data-driven solutions. They participate in interdisciplinary meetings to discuss research objectives, share analytical findings, and refine predictive models based on real-world medical feedback. Effective communication skills are essential, as they often need to explain complex data concepts to non-technical team members and ensure that solutions are both accurate and clinically relevant.

What is the difference between Cardiology Data Scientist vs Cardiologist Data Scientist?

AspectCardiology Data ScientistCardiologist Data Scientist
Required CredentialsData science degree, coding skills, healthcare analytics experienceMedical degree (MD), cardiology certification, clinical experience
Work EnvironmentHealthcare institutions, research labs, health tech companiesHospitals, clinics, cardiology departments
Employer & Industry UsageHealth tech firms, research organizations, hospitalsMedical facilities, cardiology practices, hospitals

The main difference is that a Cardiology Data Scientist combines data science expertise with healthcare analytics focused on cardiology, often working on data-driven projects. In contrast, a Cardiologist Data Scientist has medical training and specializes in clinical cardiology, integrating medical knowledge with data analysis. Both roles require healthcare familiarity, but the Cardiology Data Scientist emphasizes data skills, while the Cardiologist Data Scientist emphasizes clinical expertise.

What are the key skills and qualifications needed to thrive as a Cardiology Data Scientist, and why are they important?

To thrive as a Cardiology Data Scientist, you need a strong background in data analysis, machine learning, and a solid understanding of cardiology or biomedical science, usually supported by an advanced degree in data science, computer science, or a related field. Proficiency with programming languages such as Python or R, experience with data visualization tools, and familiarity with healthcare data standards like HL7 and electronic health records are essential. Strong communication, critical thinking, and collaboration skills help translate complex data insights into actionable clinical strategies. These competencies are crucial for developing reliable data-driven solutions that improve patient outcomes and advance cardiology research.

Are data scientists still in demand?

Data scientists, including those specializing in cardiology data analysis, remain in high demand due to the increasing reliance on data-driven decision making in healthcare. Their skills in statistical analysis, machine learning, and programming tools like Python or R are highly sought after across various industries, including medical research and clinical settings.

Sr. Data Scientist, Clinical

Prolaio

Chicago, IL • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 14 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)

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