Whoop
Staff Applied Machine Learning Scientist (Health)
Boston, MA · Staff+
Sponsorship not specifiedDetected 12 days ago
PythonAlgorithmsMachine LearningTensorFlowPyTorchscikit-learnPandasNumPyStatisticsElectrical EngineeringSensorsClinical TrialsClinical ResearchBioinformaticsMedical DevicesResearchExperimental DesignLeadershipMentoringBiostatistics
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odds of building a lasting career here
33Risky
Cap-exempt (no lottery)0
Sponsors this role66
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70
Thin sponsorship signal and lottery-bound. A low-probability bet with your clock running. Prioritize cap-exempt roles and proven entry-level sponsors first.
Lottery odds assume a STEM candidate.
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Files H-1B transfers
10 transfer filings in the last year, covering 10 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.
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About the role
- Our wearable technology collects rich physiological data, providing members with actionable insights into their recovery, training, and sleep.
- The work spans women's health, software as a medical device, wellness and longevity, member insights, and emerging health signals.
- We combine continuous physiological data with clinical research and domain expertise to ship features that are scientifically grounded and useful to millions of members.
Responsibilities
- Develop and refine approaches for time-series, longitudinal, and multimodal data, including data curation, labeling strategy, feature and representation choices, and offline evaluation that holds up under real-world noise, missingness, and population shift.
- Raise the quality and velocity of the scientists and engineers around you through design reviews, mentorship, and the judgment of when to coach someone else to champion a problem versus taking it yourself.
- drive decisions with evidence and a clear point of view on domain direction.
- Communicate trade-offs, risks, and results clearly to technical, clinical, product, and leadership audiences; prevent misalignment early; drive decisions with evidence and a clear point of view on domain direction.
- WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives.
Requirements
- Experience with wearable or physiological signals (PPG, IMU, HR/HRV, sleep, activity, temperature, or similar) or a closely related adjacent time-series domain.
- comfort with stacks such as NumPy/SciPy/pandas, scikit-learn, PyTorch/TensorFlow).
- The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office.
- Master's or PhD (or equivalent professional experience) in Biomedical Engineering, Electrical Engineering, Computer Science, Applied Mathematics, Biostatistics, Bioinformatics, Physiology, or a related quantitative or health-science field.
- 7+ years of professional experience developing algorithms, applied ML models, or statistically rigorous analyses in health, wearables, medical devices, digital health, or a closely related domain.
- Demonstrated Staff-level technical leadership: setting methodological standards others reuse, influencing multi-team outcomes, mentoring senior ICs, and making prioritization calls under uncertainty. End-to-end project ownership alone is not sufficient.
- Strong foundation in statistics (Bayesian and frequentist) and machine learning for time-series and longitudinal data, with the ability to draw defensible conclusions from observational, noisy, or otherwise messy real-world data.
- Hands-on experience designing studies or evaluation protocols end-to-end: data curation, metric choice, validation splits, subgroup and failure analysis, and documentation of assumptions and limitations.
- Strong Python skills with reproducible scientific / ML engineering hygiene (clean, reviewable code
- Clear, high-signal communicator who can move between deeply technical method discussions and cross-functional conversations with Product, clinical partners, and leadership.
- This role is based in the WHOOP office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office.
- Interested in the role, but don't meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply.
- WHOOP is an Equal Opportunity Employer and participates in E-verify https://www.e-verify.gov/ to determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
Benefits
- Lead the design, development, and validation of machine learning and statistical methods for Health features, using wearable physiological and behavioral data and related member sources.
- Frame ambiguous health and product questions into well-scoped modeling or study problems, with clear performance criteria, evaluation plans, and honest treatment of uncertainty and failure modes.
- Set the methodological and quality standard for a Health domain: reusable evaluation practices, review expectations, and documentation that others can inherit.
Company info
- At WHOOP, we're on a mission to unlock and inspire performance for life.
- At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience.
This listing is sourced directly from Whoop's careers page and normalized into a canonical job model.