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Hinge Health

Senior Growth Data Scientist - New Products

Hinge Health is hiring a Senior Growth Data Scientist - New Products in San Francisco, United States. It pays $165k-$247k a year and Level rates it ; you can apply on Hinge Health.

Level's read on this job

  • Level rates this data scientist role Little AI ●○○○: aI is not part of the work.
  • The listed pay starts close to the typical data scientist posting on Level.
  • The posting allows some remote work.
  • Tools and skills the posting cites include Databricks.
  • Level lists 74 other open roles at Hinge Health.

AI in this role

databricks

About the Role

We are seeking a Senior Data Scientist to join our Growth Data Science team and support the New Products Pod. This role will focus on building data science capabilities for a portfolio of emerging products and programs, including HingeSelect, migraines, GI, arthritis, and other new offerings, helping the team define how to position, launch, measure, and scale them. You will lead efforts in data modeling, funnel optimization, experimentation, and analytics to inform product and marketing strategy, improve member acquisition and engagement, and accelerate growth.

You will work closely with Growth Marketing, Product, Engineering, Design, and Data Science partners to answer foundational questions where the strategy and success metrics are still taking shape. This is a zero-to-one opportunity to establish measurement frameworks, build experiment-ready data foundations, and translate analytical findings into clear recommendations for high-impact decisions.

What You’ll Accomplish

New Product Growth Strategy and Measurement

  • Develop measurement frameworks and define success metrics for new products and programs where metrics are not yet established.

  • Conduct deep-dive and funnel analyses to understand member and customer behavior, explain root causes of performance changes, and identify high-value growth opportunities.

  • Collaborate with Growth Marketing and Product stakeholders to shape the strategy for how new products are positioned, marketed, launched, and scaled.

Experimentation and Optimization

  • Design and execute A/B tests and other experiments with causal guardrails to measure incremental impact while detecting and preventing cannibalization of existing digital PT engagement.

  • Build statistical models and user segmentations to help teams identify the right audiences, improve conversion, and deliver more relevant and timely experiences.

  • Use existing channel attribution and cost-efficiency frameworks, and extend them where needed, to understand the business impact of investments in new products and growth pathways.

Data Foundations and Decision Support

  • Develop robust data models and experiment-ready datasets that create a reliable source of truth for new product and growth analytics.

  • Build and maintain dashboards and self-service tools that give Growth Marketing, Product, Engineering, and leadership visibility into funnel performance and experiment results.

  • Advocate for upstream instrumentation best practices, working with Engineering to ensure events are captured with consistent schemas, timestamps, and validation.

  • Apply predictive modeling, segmentation, and other advanced analytical methods where they improve understanding of member behavior, demand, or intervention opportunities.

Basic Qualifications

  • Bachelor’s degree in Computer Science, Economics, Mathematics, Statistics, or a related technical field, or equivalent professional experience.

  • 3+ years of experience working with large datasets to solve business and technology problems and generate insights for decision-making.3+ years of experience using SQL and Python or R for data analysis and end-to-end analytical solutions.

  • Experience with A/B testing, causal inference, funnel analysis, and other experimental frameworks.

  • Experience defining metrics, building data models, and establishing measurement frameworks in ambiguous or greenfield environments.

Preferred Qualifications

  • Knowledge of machine learning techniques for predictive modeling, segmentation, forecasting, and recommendation systems.

  • Prior experience in growth or product analytics for new product launches, partner analytics, referral tracking, or marketplace data science.

  • Experience defining event taxonomies and data architecture for new product surfaces.

  • Knowledge of cloud infrastructure and tools such as AWS, Databricks, Airflow, and dbt.

  • Familiarity with experimentation and visualization platforms such as Statsig, Split, Optimizely, Mode, Tableau, or similar.

  • Background in healthcare, digital health, wellness, or member engagement analytics.

  • Experience using AI-assisted coding tools for rapid prototyping, analysis, and production development.

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.

How we rate this

Senior Growth Data Scientist - New Products at Hinge Health rates 17 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

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