Biostatistician, Quantitative Epidemiology

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.g., GCP), metric definition, and analytical validation for production use.

• Comfort operating in a fast-moving, cross-functional environment with evolving priorities.

Hinge Health Hybrid Model

We believe that remote work and in-person work have their own advantages and disadvantages, and we want to be able to leverage the best of both worlds. Employees in hybrid roles are required to be in the office 3 days per week, for the full 8 hours of a typical business day. The San Francisco office has a dog-friendly workplace program.

About Hinge Health

At Hinge Health, we’re using technology to scale and automate the delivery of healthcare, starting with musculoskeletal (MSK) conditions, which affect over 1.7 billion people worldwide. Our AI-powered, human-centered care model spans MSK, pelvic health, gastrointestinal (GI) and migraine care. With over 60 partnerships with health plans, PBMs and other ecosystem partners, Hinge Health is available to over 25 million people across more than 2,900 employers. The company is headquartered in San Francisco with additional offices in Montreal and Bangalore. Learn more at hingehealth.com.

What You’ll Love About Us

• Inclusive healthcare and benefits: On top of comprehensive medical, dental, and vision coverage, we offer employees and their family members help with gender-affirming care, tools for family and fertility planning, and travel reimbursements if healthcare isn’t available where you live.

• Planning for the future: Start saving for the future with our traditional or Roth 401k retirement plan options which include a 2% company match.

• Modern life stipends: Manage your own learning and development.

• Grow with us: Grow with us through discounted company stock through our ESPP with easy payroll deductions.

Culture & Engagement

Hinge Health is an equal opportunity employer and prohibits discrimination and harassment of any kind. We make employment decisions without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, age, veteran status, disability status, pregnancy, or any other basis protected by federal, state or local law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. We provide reasonable accommodations for candidates with disabilities. If you feel you need assistance or an accommodation due to a disability, let us know by reaching out to your recruiter.

By submitting your application you are acknowledging we are using your personal data as outlined in the personnel and candidate privacy policy.

Beware of Phishing Attempts: We've noticed an increase in phishing where fraudsters impersonate employees and send fake job offers to steal sensitive information. We'll never ask for financial details during the hiring process and only use "@hingehealth.com" emails. If you receive a suspicious offer, stop communication and report it to the US FBI Internet Crime Complaint Center. To verify an email from our recruiting team, forward it to security@hingehealth.com.

The Biostatistician, Quantitative Epidemiology role designs and analyzes studies to assess the clinical, member, and cost outcomes of digital musculoskeletal care. It turns longitudinal and real-world data into reproducible evidence and decision-ready findings in partnership with clinical, product, data, and research teams.

Role at a glance

Skills mentioned

What you will likely work on

• Create analysis plans for observational, interventional, clinical, and product-impact studies.
• Build and validate analyses using R, Python, or SQL, with reproducible methods and workflows.
• Analyze longitudinal and real-world datasets from preparation through modeling and interpretation.
• Define hypotheses, metrics, and success criteria tied to clinical and business decisions.
• Advise teams on study design, statistical methods, and interpretation across product and clinical initiatives.
• Contribute to manuscripts, abstracts, and presentations communicating clinical and product outcomes.
• Improve the quality, transparency, and validation of evidence-generation practices.

Good fit signals

• You have an MS or PhD in biostatistics, statistics, epidemiology, or a closely related quantitative field.
• You meet one of the stated experience paths: PhD with 2+ years, or master's with 6+ years, in applied study design and analysis.
• You can work across study design, modeling, and interpretation and communicate findings to technical and non-technical audiences.
• Experience with real-world, administrative claims, or clinical data is especially relevant; healthcare, clinical research, or digital health experience is preferred.
• Familiarity with causal inference, survival analysis, mixed-effects models, or Bayesian methods is helpful, as is publication or regulatory-submission experience.