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Principal Applied Machine Learning Scientist

Omada Health · Remote, USA · US

Clinical Data Science
Remote
Not yet analysed
Demand85
Career growth90
Healthcare fit45
Remote potential80
5-year outlook
Principal-level ML scientists in digital health typically command top-tier compensation, often exceeding $200k base with equity, and the demand for such expertise is growing as healthcare AI adoption accelerates. Exact figures vary by location and company, but the outlook is strong.
Clinical license
Not required
Applicant reach
narrow
Seniority
senior
Employment type
Date found
2026-08-26

Intelligence details

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Why this is worth applying to

Clinicians with a strong quantitative background (e.g., MD/PhD, PhD in biostatistics) and deep ML experience should consider this role, as it offers the chance to directly shape chronic disease management algorithms. However, most clinicians without formal ML research training will not meet the requirements.

Who should apply

Physicians or allied health professionals with a Ph.D. in a quantitative field (CS, statistics, biostatistics) and a proven track record in applied ML research, especially in healthcare or digital health settings.

CV angle

Emphasize any clinical domain expertise as a differentiator for understanding healthcare data and clinical outcomes, while highlighting your ML research publications, production deployments, and experience with longitudinal or time-series data. Frame clinical experience as 'domain expertise' that informs algorithm design and clinical interpretability.

Skills to highlight

  • Python
  • Machine Learning
  • Time-series modeling
  • Causal inference
  • Reinforcement learning
  • AWS SageMaker
  • Healthcare data
  • Research leadership

Role summary

Lead applied ML research at Omada Health to build health trajectory prediction models and next-best-action algorithms that optimize chronic disease interventions, requiring deep technical expertise and cross-functional collaboration.

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