Senior Research Scientist

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