Whoop
Senior Manager, ML Health - Insights
Boston, MA · Senior · Full-time
Sponsorship not specified$170k-$230kDetected 12 days ago
AlgorithmsMachine LearningPerformance ManagementLeadership
Stay score
odds of building a lasting career here
55Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role66
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70
Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
Personalize to your clock →Employer immigration record
from this employer's Department of Labor filings
Green-card filing pattern in this occupation
Context, not a finding about this posting: of this employer's 3 green-card filings in this occupation, 100% were for a worker who already held the job.
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.
Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.
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About the role
- The work spans women's health, wellness and longevity, member insights, emerging health signals, and software as a medical device.
- Interested in the role, but don't meet every qualification?
Responsibilities
- Build the team: lead hiring across science and engineering roles, calibrate the bar for each craft, and shape onboarding, leveling, and growth practices.
- Develop the next layer of leadership: coach senior ICs (and managers, as the scope grows), manage performance with clarity and care, and create the conditions for people to operate above their level.
- Own the risk posture for the team: anticipate execution, technical, and people risks, design mitigation into how the team operates, and keep senior leadership clearly informed of the most consequential decisions.
- Build and continuously raise AI-enabled workflows that create measurable leverage across the team, for development, evaluation, documentation, and stakeholder communication.
Requirements
- Demonstrated ability to set direction and make timely prioritization calls under uncertainty, keeping team focused on the highest-leverage work.
- 7+ years of experience in machine learning, applied science, or software engineering, with 3+ years managing engineering and/or science teams.
- Demonstrated track record managing highly senior ICs: hiring, performance management, and developing people who in turn raise the bar around them.
- Deep familiarity with the ML development lifecycle (data collection, model training, evaluation, validation, deployment, and monitoring), sufficient to evaluate the most important technical and methodological decisions the team makes.
- Experience shipping algorithms or ML-enabled product in health, wearables, digital health, or a closely related applied domain.
- Demonstrated AI-tooling sophistication: a track record of building or adopting AI-enabled workflows that materially improved team speed, quality, or decision confidence.
- Clear, high-signal communicator who can move fluidly between technical ML discussions and executive-level summaries of risk, trade-offs, and direction.
- Depth in a Health domain WHOOP already works in preferred (member insights, women's health, cardiometabolic or respiratory health, sleep, strength / healthspan, neuroscience, or related physiological time-series work).
- Preferred experience as a counterpart to Product on ambiguous health or member-insight problems: scoping, sequencing, and pushing back when a claim is not supportable.
- Familiarity with clinical validation, evidence packages, or Digital Health partnership on higher-stakes health features preferred.
- 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.
Nice to have
- Applied ML Scientists and ML Engineers work as a production unit:
- You will stay close enough to the ML lifecycle to evaluate the team's most important decisions without becoming the default contributor.
- Bachelor's degree in Computer Science, Engineering, Applied Math, Biomedical Engineering, or a related field
- advanced degree preferred.
Compensation
- The WHOOP compensation philosophy is designed to attract, motivate, and retain exceptional talent by offering competitive base salaries, meaningful equity, and consistent pay practices that reflect our mission and core values.
Benefits
- Own delivery, team health, and people outcomes across Health ML workstreams on a mixed Applied ML Scientist and ML Engineer team.
- Set the standard for how Health ML gets built: work quality, evaluation rigor, review practices, and an operating model that holds as people and workstreams change.
- Partner directly with Product (and with clinical, software, and Digital Health partners as the work requires) to align on roadmap, evidence, and sequencing
- Define and own the operating model: planning cadences, design reviews, decision forums, and quality gates appropriate to member-facing health ML.
Company info
- Partner directly with Product (and with clinical, software, and Digital Health partners as the work requires) to align on roadmap, evidence, and sequencing; broker trade-offs between iteration speed, scientific integrity, and member value.
- Represent the team's work credibly to executive and cross-functional audiences with brevity, evidence, and clarity.
This listing is sourced directly from Whoop's careers page and normalized into a canonical job model.