Job Opportunities API

1 in 4 people in the US have a treatable mental health condition, but most providers don't accept insurance, making therapy too expensive for most people. Headway’s mission is to fix this by building a new mental healthcare system everyone can access. We started by solving the biggest barrier to care: insurance. The admin work - credentialing, claims, payment reconciliation - is a nightmare. We've automated that. But we're going further. Over 75,000 providers across all 50 states run their practice on our software, serving over 1 million patients. We are building the best tools for therapists to run their entire practice, reimagining the experience of finding a therapist, and investing in the platform foundations to enable this at scale. We aren't just a billing layer; we are becoming the platform where care actually happens. We're a Series D company with $325M+ in funding (a16z, Accel, Spark Capital, etc.), looking for exceptional people to help us achieve this mission. We want your time here to be the most meaningful experience of your career. Join us, and help change mental healthcare for the better. ABOUT THE ROLE Join us to build the measurement and decision engine for patient growth. As a Staff Data Scientist, Growth, you will be the senior analytical and strategic leader who makes marketing performance legible, credible, and actionable. You will partner closely with Growth Marketing leadership and channel owners across paid, lifecycle, and organic, plus Finance, Product, and Engineering. Your job is to help Headway answer the questions that matter: - What is truly incremental? - Where should we invest next? - What is driving performance shifts? - How do we scale what works without fooling ourselves? You will build the frameworks, analyses, and modeling approaches that enable the marketing team to move faster with confidence. This is high-stakes decision support for a growth engine that needs to compound and certainly not a dashboard-only role or “just attribution” role.  WHAT YOU WILL DO - Own incrementality measurement across channels. Design and analyze geo tests, holdouts, lift tests, and quasi-experimental approaches when randomized tests are not feasible. Define clear guardrails, decision rules, and what “good” looks like. - Build a marketing measurement system that leaders trust. Define canonical metrics (CAC, LTV, payback, conversion, retention, capacity-adjusted ROI), ensure definitions are consistent, and create a clear measurement narrative that aligns Marketing, Finance, and Product. - Turn ambiguity into a plan. When performance changes, you will diagnose why, quantify contributing drivers, and recommend concrete actions. You will be the person who can say, “Here’s what moved, here’s why we believe it moved, and here’s what we do next.” - Develop and evolve modeling approaches where they create leverage. Build practical models such as LTV and retention forecasting, cohort value prediction, causal uplift models for lifecycle, and marketing mix modeling when appropriate. Focus on models that survive contact with reality: calibration, backtesting, and decision usefulness. - Partner with Engineering on the measurement plumbing. Improve event instrumentation, identity resolution assumptions, offline conversion integration, and data quality monitoring so measurement is robust. Advocate for minimal, decision-critical requirements that unlock reliable learning. - Design learning loops that scale. Create repeatable experimentation and analysis templates for channel and creative testing, including measurement of message by audience by surface. Increase testing velocity without lowering the truth standard. - Influence strategy, not just reporting. Bring an evidence-based point of view on channel allocation, growth constraints, saturation, diminishing returns, and the tradeoffs between short-term acquisition and long-term retention and care outcomes. - Uplevel