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RESPONSIBILITIES

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• Lead end-to-end research projects from hypothesis formulation through analysis, interpretation, and communication
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• Analyze large-scale, longitudinal physiological and behavioral datasets to identify meaningful patterns and insights
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• Develop and evaluate models that characterize individual variability and predict future physiological states
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• Translate research findings into clear, actionable recommendations that inform product direction and algorithm development
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• Collaborate closely with product, engineering, and data science teams to ensure research is interpretable and aligned with real-world use cases
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• Contribute to the design and execution of research programs
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• Produce high-quality scientific outputs, including internal reports, white papers, and peer-reviewed publications
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• 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.
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• Help define research standards, methodologies, and best practices across the team
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QUALIFICATIONS

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• <li>PhD (or equivalent experience) in a quantitative or health-related field (e.g., Epidemiology, Biostatistics, Biomedical Engineering, Neuroscience, Computer Science, or related disciplines),&nbsp;</li>
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• 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)
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• Demonstrated ability to design hypothesis-driven analyses and translate findings into clear conclusions
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• Proficiency in statistical modeling and/or machine learning methods and demonstrated experience using Python or R
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• Significant hands-on experience with advanced modeling techniques for longitudinal/time-series data, such as probabilistic methods, Bayesian inference, and/or causal inference
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• Ability to work across disciplines and communicate effectively with both technical and non-technical stakeholders
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• Experience connecting data analysis to real-world applications (product, wellness, clinical, or operational)
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• Strong written and verbal communication skills
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