Senior Research Scientist

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    "city": "Boston",
    "region": "MA",
    "country": "United States",
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{
  "lists": [
    {
      "text": "RESPONSIBILITIES:",
      "content": "<div>\n\n<li>\n<p>Lead end-to-end research projects from hypothesis formulation through analysis, interpretation, and communication</p>\n</li>\n<li>\n<p>Analyze large-scale, longitudinal physiological and behavioral datasets to identify meaningful patterns and insights</p>\n</li>\n<li>\n<p>Develop and evaluate models that characterize individual variability and predict future physiological states</p>\n</li>\n<li>\n<p>Translate research findings into clear, actionable recommendations that inform product direction and algorithm development</p>\n</li>\n<li>\n<p>Collaborate closely with product, engineering, and data science teams to ensure research is interpretable and aligned with real-world use cases</p>\n</li>\n<li>\n<p>Contribute to the design and execution of research programs</p>\n</li>\n<li>\n<p>Produce high-quality scientific outputs, including internal reports, white papers, and peer-reviewed publications</p>\n</li>\n<li>\n<p>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.</p>\n</li>\n<li>\n<p>Help define research standards, methodologies, and best practices across the team</p>\n</li>\n\n</div>"
    },
    {
      "text": "QUALIFICATIONS:",
      "content": "\n<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>\n<li>\n<p>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)</p>\n</li>\n<li>\n<p>Demonstrated ability to design hypothesis-driven analyses and translate findings into clear conclusions</p>\n</li>\n<li>\n<p>Proficiency in statistical modeling and/or machine learning methods and demonstrated experience using Python or R</p>\n</li>\n<li>\n<p>Significant hands-on experience with advanced modeling techniques for longitudinal/time-series data, such as probabilistic methods, Bayesian inference, and/or causal inference</p>\n</li>\n<li>\n<p>Ability to work across disciplines and communicate effectively with both technical and non-technical stakeholders</p>\n</li>\n<li>\n<p>Experience connecting data analysis to real-world applications (product, wellness, clinical, or operational)</p>\n</li>\n<li>\n<p>Strong written and verbal communication skills</p>\n</li>\n"
    }
  ],
  "country": "US",
  "createdAt": 1778506631762,
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  "categories": {
    "team": "Machine Learning & Research",
    "location": "Boston, MA",
    "commitment": "Full Time",
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