Easy Apply
Easy Apply
Similar Jobs at WHOOP
Fitness • Hardware • Healthtech • Sports • Wearables
Lead design projects at WHOOP, focusing on AI-driven user experiences. Responsibilities include user research, prototyping, and collaboration with cross-functional teams.
Top Skills:
Ai ToolsFigmaLow-Code ToolsNo-Code ToolsUx Research
Fitness • Hardware • Healthtech • Sports • Wearables
Lead complex hardware projects from concept to market, managing multi-disciplinary teams, ensuring technical excellence, and coordinating with cross-functional departments.
Top Skills:
Data ScienceElectrical EngineeringFirmwareMechanical EngineeringPcbasSupply Chain ManagementWireless Components
Fitness • Hardware • Healthtech • Sports • Wearables
Lead a data science team to deliver impactful health features, manage projects, optimize resources, and mentor team members in a collaborative environment.
Top Skills:
AlgorithmsData ScienceMachine LearningPythonSQLStatistical Analysis
At WHOOP, we are on a mission to unlock human performance and healthspan. Our platform empowers members to make data-driven decisions that improve health, recovery, and performance by offering unparalleled insights into their unique physiology.
Data is the foundation of WHOOP's innovation, and our Machine Learning (ML) platform is the connective tissue that enables data to power real-time insights, personalized algorithms, and breakthrough science. As a Senior Data & ML Observability Analyst, you will lead initiatives that ensure our physiological models and data pipelines are transparent, resilient, and impactful. Your work will support mission-critical ML products, ensure stakeholder confidence through robust monitoring, and champion innovation in observability tooling.
RESPONSIBILITIES:
- Build Observability Frameworks: Design, implement, and maintain scalable observability solutions to track the health and performance of offline and real-time ML models.
- Monitor Data & ML Quality: Develop dashboards and alerts to track data quality, distributional shifts, and model drift. Partner with teams to investigate anomalies and recommend solutions.
- Cross-Functional Collaboration: Work closely with data scientists, ML engineers, product managers, and software teams to define observability requirements, translate use cases, and ensure seamless integration.
- Support Algorithm Deployments: Guide new algorithm rollouts with monitoring strategies that validate performance across WHOOP diverse member base.
- AI-Driven Innovation: Leverage modern AI tools (e.g., Copilot, Cursor, ChatGPT) to automate observability workflows, optimize monitoring pipelines, and uncover new insights.
- Mentorship Opportunity: Serve as a mentor to other analysts as the team grows, offering guidance and leadership in best practices and career development.
- Continuous Improvement: Stay current on emerging technologies, observability trends, and industry best practices to enhance WHOOP's data and ML infrastructure.
QUALIFICATIONS:
- Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field.
- 4+ years of experience in data analytics, data engineering, or ML operations, with a focus on data quality & model performance observability.
- Strong SQL & DBT skills; experience with Snowflake is highly preferred.
- Proficiency dealing with large data sets via programming languages like Python.
- Experience with data visualization platforms such as Sigma, HEX, or equivalent.
- Proven experience on providing actionable insights for different stakeholders based on a variety of data sets.
- Familiarity with ML lifecycles, performance monitoring, and basic modeling concepts.
- Experience working with physiological or time-series data is a strong plus.
- Strong interpersonal and communication skills; comfortable translating technical observations into business value.
- Keen attention to detail, structured problem-solving approach, and an iterative mindset.
- Experience mentoring or coaching junior team members.
- Understanding of MLOps best practices including CI/CD pipelines for model deployment and validation.
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 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.
WHOOP Boston, Massachusetts, USA Office
1 Kenmore Sq, Boston, MA, United States, 02215
What you need to know about the Boston Tech Scene
Boston is a powerhouse for technology innovation thanks to world-class research universities like MIT and Harvard and a robust pipeline of venture capital investment. Host to the first telephone call and one of the first general-purpose computers ever put into use, Boston is now a hub for biotechnology, robotics and artificial intelligence — though it’s also home to several B2B software giants. So it’s no surprise that the city consistently ranks among the greatest startup ecosystems in the world.
Key Facts About Boston Tech
- Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
- Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
- Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
- Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories
