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Senior Data Scientist, Clinical

Prolaio
Full Timesenior
Chicago, ILPosted 28 days ago

Role Overview

Prolaio is hiring a Senior Data Scientist, Clinical. This is a full-time role in Chicago. Part of Prolaio's Risk hiring, posted 4 weeks ago. Full responsibilities, required qualifications, and the apply link are listed in the description below.

Salary Context

Salary is not disclosed in this posting. Market median for Senior-level Risk roles is $108k-$160k (based on 28 comparable listings). Many employers share specifics during the interview process or after an initial screen.

Resume Keywords to Include

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PythonRSQLGitPyTorchscikit-learnPipelineEHR

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)

About Prolaio

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Prolaio

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Frequently Asked Questions

How do I apply for the Senior Data Scientist, Clinical position at Prolaio?

Use the Apply button above to submit your application directly to Prolaio. Most applications take less than 5 minutes if your resume and contact details are ready, and you'll be routed to the employer's official application system to finish.

Where is the Senior Data Scientist, Clinical position at Prolaio located?

This position is based in Chicago. Prolaio has not indicated remote or hybrid options for this role, so candidates should plan for on-site work.

What does a Senior Data Scientist, Clinical at Prolaio earn?

Prolaio has not disclosed a salary range in this posting. Many employers share specifics later in the interview process; you can also ask during a recruiter screen if compensation transparency is important to you.

When was the Senior Data Scientist, Clinical role at Prolaio posted?

This role was posted on June 11, 2026 (28 days ago). It's still listed as actively hiring; we re-confirm openings against the source system multiple times per day and remove closed roles.

How much experience does the Senior Data Scientist, Clinical role at Prolaio require?

This is a senior-level position. Most senior roles call for 5+ years of directly relevant experience. Prolaio lists their specific requirements in the description below, so review the must-have qualifications closely before applying.

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