Applied Research Scientist, Clinical AI at RhythmScience
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Jul 21, 2026
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Jul 22, 2026
What this job asks for AI summary
A machine learning role focused on cardiac remote monitoring software, responsible for taking models from research to production, building population-level outcome analytics from real-world patient device data, and designing rigorous clinical evaluation frameworks. The work spans model deployment, PHI-compliant data handling, and backtesting against clinical notes. Best suited to someone with hands-on experience shipping biomedical or clinical ML systems end to end.
Senior level · Remote · Master's required · Full-time
“or” means any one of them counts — you don't need all of them.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Roughly 28,700 people nationally plausibly meet what this posting asks for (data scientists). range 5,900–43,000
Applicant volume Heavy — This req sits in a large pool with little in its requirements to thin it, and auto-apply tools fire at everything in the occupation. Applying early and leading with the rare skills below is what gets read.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $122,874 (middle half $87,544–$162,374).
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (7)
The title 'Applied Research Scientist, Clinical AI' carries no explicit seniority level word, so the title states no level. However, the scope — owning model quality end-to-end, deploying to production, building population analytics, and reporting directly to the Head of Engineering — supports a Senior-level assessment.
The degree requirement is stated as 'Advanced degree in related field' (i.e., Master's or higher) in the Required Skills & Qualifications section, so it is treated as a hard gate at the Master's level.
PyTorch is listed with '(or equivalent framework)' — well-known interchangeable deep learning frameworks (TensorFlow, JAX) are captured in alternatives.
Domain expertise in clinical/biomedical ML is listed as required but names several data modalities (EHR, time-series, sensor, imaging) as interchangeable examples; these are captured as alternatives on a single skill.
Compensation is explicitly stated as 'currently being benchmarked' with no figures provided — no comp range is available.
The alternative occupation reflects genuine ambiguity: the role ships production models integrated with a backend application (15-1252 signal) but is primarily framed around ML research, evaluation methodology, and clinical data science (15-2051 signal). 15-2051 is the primary classification.
The posting mentions significant overlap with PST hours but is fully remote across US time zones; no specific metro is associated.
Read the full posting
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