Senior Manager, Data Science - Patient Growth

Headway
New York, New York, United States; San Francisco, California, United States; Seattle, Washington, United StatesPosted 27 March 2026

Job Description

Headway’s mission is a big one – to build a new mental health care system everyone can access. We’ve built technology that helps people find great therapists with the first software-enabled national network of providers accepting insurance. 1 in 4 people in the US have a treatable mental health condition, but the majority of providers don’t accept insurance, making therapy too expensive for most people. Headway is building a new mental healthcare system that everyone can access by making it easy for therapists to accept insurance and scale their practice. Headway was founded in 2019. Since then, we’ve grown into a diverse, national network of over 60,000 mental healthcare providers across all 50 states who run their practice on our software and have served over 1 million patients. We’re a Series D company with over $325m in funding from a16z (Andreessen Horowitz), Accel, GV (formerly Google Ventures), Spark Capital, Thrive Capital, Forerunner Ventures and Health Care Service Corporation. We want your time here to be the most meaningful experience of your career. Join us, and help change mental healthcare for the better. ACTION FOR BIZ RECRUITERS ONLY: Please remove the "Are you open to relocating?" question in the custom application questions section before posting the job on the careers site. This is only a required question for RD roles. About the Role Headway's patient growth engine is scaling fast, and we need a senior analytics leader who can make marketing performance legible, credible, and actionable. As Senior Manager, Data Science - Patient Growth , you will own the marketing analytics strategy that helps Headway acquire patients efficiently and at scale. You will build and lead a team that answers the questions Growth Marketing, Finance, and Product need answered: what's truly incremental, where should we invest next, and how do we scale what works without fooling ourselves. You will report to the Director of Data Science, Patient and partner closely with Growth Marketing leadership, Finance, Product, and Engineering. You will have real accountability for how Headway measures, evaluates, and improves patient acquisition. What you'll do at Headway Own Marketing Measurement Growth Analytics Define and own the measurement strategy for patient acquisition across paid, lifecycle, and organic channels, including incrementality testing, CAC efficiency, channel performance, and conversion quality. Design and analyze geo tests, holdouts, lift studies, and quasi-experimental approaches to distinguish correlation from true marketing impact. Establish clear guardrails, decision rules, and evidence standards. Build the canonical metrics framework (CAC, LTV, payback, cohort value, capacity-adjusted ROI) that aligns Marketing, Finance, and Product on what "good" looks like and how to compare performance over time. When performance shifts, diagnose why, quantify contributing drivers, and recommend concrete next steps. Be the person who can say: "Here's what moved, here's why we believe it, and here's what we do next." Build Models Systems That Scale Develop and evolve practical modeling approaches (LTV forecasting, cohort value prediction, causal uplift models, saturation analysis) focused on calibration, backtesting, and decision usefulness. Partner with Engineering on measurement infrastructure: event instrumentation, identity resolution, offline conversion integration, and data quality monitoring so that learning is reliable. Create repeatable experimentation and analysis templates for channel and creative testing that increase velocity without lowering the truth standard. Lead and Grow the Team Lead, coach, and develop a team of data scientists starting at 2 and scaling to up to 10 as needs are identified through 2026. Set clear expectations for ownership, communication, and impact. Coach senior ICs, provide strong technical review, and model what great analytical work looks like, from hypothesis framing t ... (truncated, view full listing at source)
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