Senior/Staff Data Scientist
Grow TherapySan Francisco$182k – $228kPosted 19 April 2026
Job Description
About Us:
Grow Therapy is on a mission to serve as the trusted partner for therapists growing their practice, and patients accessing high-quality care. Powered by technology, we are a three-sided marketplace that empowers providers, augments insurance payors, and serves patients. Following the mass increase in depression and anxiety, the need for accessibility is more important than ever. To make our vision for mental healthcare a reality, we’re building a team of entrepreneurs and mission-driven go-getters. Since launching in February 2021, we’ve empowered more than ten thousand therapists and hundreds of thousands of clients across the country and insurance landscape. We’ve raised more than $178mm of funding from Sequoia Capital, Transformation Capital, TCV, SignalFire, and others.
The Opportunity:
Grow Therapy is seeking a Senior/Staff Data Scientist to build the data foundations that power the next phase of our provider and care experience. In this role, you will work across the full data science stack, from causal inference and NLP to LLM pipelines and ML productionization, tackling open-ended problems that directly shape how patients and providers experience Grow Therapy. Your work will influence product strategy, marketplace quality, and long-term investment decisions across the company.
What You’ll Be Doing:
Build and ship ML models end-to-end , from feature engineering to production, across ranking, matching, and predictive systems with measurable business impact.
Develop and deploy LLM-powered solutions applied to real-world mental health workflows, including evaluation frameworks and quality measurement.
Apply causal inference and behavioral analysis to understand what drives user retention, engagement, and overall platform health.
Design and maintain centralized monitoring infrastructure , OKR tracking, and impact-sizing frameworks that keep the business oriented around outcomes.
Partner with Product, Engineering, and Operations to move quickly from ambiguous problems to scalable, production-ready data solutions.
Leverage Grow Therapy's unique and rich dataset to build personalized experiences that drive meaningful mental health outcomes for patients.
You’ll Be a Good Fit If:
3+ years of industry experience building ML/AI systems at scale.
Proven track record deploying production ML models with measurable business impact. Hands-on experience with NLP, LLMs, and GenAI techniques.
Experience driving product or growth decisions through deep user understanding, funnel decomposition, or marketplace dynamics.
Passion for navigating ambiguity and working cross-functionally in fast-moving environments where data science directly influences strategy.
Excited about improving access to mental health care and motivated by building human-centered AI-enhanced experiences that support therapists and patients.
Role Details:
Employment Type: Full Time, Exempt Base Compensation: The base compensation range for this position is:
Hybrid Commitment: $182,000–$228,000 USD USD Annually
This role can be hybrid (onsite from our San Francisco hub location three days per week: Tuesday, Wednesday, Thursday) including travel 2–3 times per year (e.g., company and department off-sites).
Full Time Employee Benefits:
Comprehensive Health Coverage: Medical, dental, and vision insurance, plus life and disability coverage.
Parental Leave Family Support: Up to 18 weeks paid leave and a new child stipend.
Financial Wellness: 401(k) program and equity opportunities.
Meals Home Office Support: Stipends for home office setup and ongoing funds for meals, with tailored perks for both remote and in-office employees.
Time Off to Recharge: Flexible PTO, 12 paid holidays, and a full winter break week.
Wellness Development: Annual stipends to put towards personal professional growth.
Mental Physical Health Support: No-cost access to therapy through the Grow platform, weekly flexible hours for self-care (“Mental ... (truncated, view full listing at source)
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