Growth Data Scientist
US$165,000 – US$247,000 / yr base salary
Posted 24 Aug 2026
Advertised as “Senior Growth Data Scientist - New Products”
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 3+ yrs
- Management level
- Individual contributor
- Employment
- Hybrid
- Contract
- Full-time
| Base salary | US$165,000 – US$247,000 / yr |
|---|
Field of studyComputer Science, Economics, Mathematics, Statistics (or related)
Study levelBachelor's
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
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Develop measurement frameworks and define success metrics for new products and programs where metrics are not yet established.
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Conduct deep-dive and funnel analyses to understand member and customer behavior, explain root causes of performance changes, and identify high-value growth opportunities.
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Collaborate with Growth Marketing and Product stakeholders to shape the strategy for how new products are positioned, marketed, launched, and scaled.
Experimentation and Optimization
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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.
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Build statistical models and user segmentations to help teams identify the right audiences, improve conversion, and deliver more relevant and timely experiences.
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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
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Develop robust data models and experiment-ready datasets that create a reliable source of truth for new product and growth analytics.
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Build and maintain dashboards and self-service tools that give Growth Marketing, Product, Engineering, and leadership visibility into funnel performance and experiment results.