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Senior Research Scientist

Whoop

Whoopwhoop.com

Senior Research Scientist

Posted 2 months ago

This job is still taking applications, but it's been up a while.

About the job

WHOOP is dedicated to unlocking human performance and healthspan through physiological data analysis. The Senior Research Scientist will lead hypothesis-driven projects, analyze large datasets, and collaborate with multiple teams to develop insights that enhance product offerings and scientific rigor.

Requirements

  • PhD or equivalent in a health-related field
  • Experience with longitudinal data modeling
  • Proficiency in Python or R
  • Strong communication skills
  • Ability to work across disciplines

Qualifications

  • PhD in Epidemiology, Neuroscience, or related
  • Experience in health science and public health
  • Hands-on with advanced modeling techniques
  • Ability to collaborate with technical and non-technical teams
  • Excellent written/verbal skills

Full job description

RESPONSIBILITIES:

  • Lead end-to-end research projects from hypothesis formulation through analysis, interpretation, and communication

  • Analyze large-scale, longitudinal physiological and behavioral datasets to identify meaningful patterns and insights

  • Develop and evaluate models that characterize individual variability and predict future physiological states

  • Translate research findings into clear, actionable recommendations that inform product direction and algorithm development

  • Collaborate closely with product, engineering, and data science teams to ensure research is interpretable and aligned with real-world use cases

  • Contribute to the design and execution of research programs

  • Produce high-quality scientific outputs, including internal reports, white papers, and peer-reviewed publications

  • Serve as a senior technical leader, providing guidance and mentorship to junior scientists and contributing to raising the bar for scientific rigor across the team.

  • Help define research standards, methodologies, and best practices across the team


    • QUALIFICATIONS:

    • PhD (or equivalent experience) in a quantitative or health-related field (e.g., Epidemiology, Biostatistics, Biomedical Engineering, Neuroscience, Computer Science, or related disciplines), 

    • Strong background in health science, with grounding in public health and clinical concepts, and experience modeling longitudinal or time-series data (e.g., within-person variability in real-world settings)

    • Demonstrated ability to design hypothesis-driven analyses and translate findings into clear conclusions

    • Proficiency in statistical modeling and/or machine learning methods and demonstrated experience using Python or R

    • Significant hands-on experience with advanced modeling techniques for longitudinal/time-series data, such as probabilistic methods, Bayesian inference, and/or causal inference

    • Ability to work across disciplines and communicate effectively with both technical and non-technical stakeholders

    • Experience connecting data analysis to real-world applications (product, wellness, clinical, or operational)

    • Strong written and verbal communication skills

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