Biostatistician, Quantitative Epidemiology

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About the role

THE OPPORTUNITY Join the team building the evidence engine behind Hinge Health’s digital musculoskeletal (MSK) care. As a Biostatistician focusing on Quantitative Epidemiology, you’ll design and execute rigorous studies that demonstrate how our products improve outcomes, experiences, and costs for millions of members. You’ll partner closely with clinical, product, data, and research teams to shape strategy through high-quality analyses, turning complex real-world data into clear, actionable insights for decision-makers across the business. WHAT YOU’LL ACCOMPLISH In your first 3 months, you will: - Design statistical analysis plans for observational and interventional studies, clinical evaluations, and product impact analyses in collaboration with clinical, product, and data partners. - Implement and validate core analysis workflows in R/Python/SQL for key in-flight studies, ensuring methods are appropriate and reproducible. - Build strong cross-functional relationships with clinical, research, and product stakeholders to understand their goals and data sources. By 6 months, you will: - Lead end-to-end analyses of complex longitudinal and real-world datasets, from study design and data preparation through modeling and interpretation. - Define and refine metrics, hypotheses, and success criteria that connect statistical rigor to clear business and clinical decisions. - Establish and document reproducible analysis pipelines, helping raise the bar on analytical quality, transparency, and speed across the team. By your first year, you will: - Serve as a go-to partner for complex statistical questions, advising on study design, method selection, and interpretation for multiple product and clinical initiatives. - Support manuscripts, abstracts, and presentations that showcase Hinge Health’s clinical and product outcomes to customers, partners, and the broader research community. - Help continuously improve how Hinge Health generates, validates, and communicates evidence, so stakeholders can act quickly and confidently on the insights you provide. WHO YOU ARE - A rigorous applied statistician who is comfortable moving from study design to modeling to clear interpretation, with a strong focus on real-world impact rather than purely theoretical work. - A collaborative, “learn-it-all” partner who seeks feedback, iterates on methods, and stays current on statistical best practices in clinical, digital health, and real-world evidence settings. - An effective communicator who can translate complex statistical results into meaningful stories and recommendations for both technical and non-technical stakeholders. - An owner-operator who brings strong judgment, takes accountability for the quality of your analyses, and helps raise the bar on evidence generation across teams. BASIC QUALIFICATIONS - MS or PhD in Biostatistics, Statistics, Epidemiology, or a closely related quantitative field. - PhD and 2+ (OR Masters and 6+) years of applied experience designing and analyzing observational, clinical, or product impact studies, ideally using real-world data (i.e., administrative claims) or clinical data. Proficiency in at least one major statistical programming language (R, Python, or SAS) and demonstrated ability to communicate findings to both technical and non-technical audiences. PREFERRED QUALIFICATIONS - Experience working in regulated healthcare, clinical research, or digital health environments. - Familiarity with one or more of: causal inference, survival analysis, mixed-effects models, or Bayesian methods. - Experience leading and publishing peer-reviewed publications, conference abstracts, or regulatory submissions. - Knowledge of data quality best practices, regulatory guidelines (e

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