Staff Data Scientist

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 90,000 providers across all 50 states run their practice on our software, serving over 2.6 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, and building much of it with AI. 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 decision engine for better mental health outcomes.

As a Staff Data Scientist, you will be a senior technical and strategic leader for how Headway measures, learns, and improves. You will own the hardest and most ambiguous product questions, shape how we define success, and drive decisions that cut across multiple teams and product surfaces. You will not only run the analyses, you will influence what we build, how we evaluate it, and how we scale what works.

This role is for someone who can zoom in to debug a metric definition and zoom out to design a measurement strategy for a major product area, then bring the organization along with them.

What you will do

Own a product measurement strategy. Define north star and input metrics for a major product area (or multiple surfaces), align stakeholders on definitions, and build conviction in what "good" looks like.

Lead multi-team initiatives. Drive cross-functional work where the right answer is not obvious and the path is not linear, and ensure we land measurable outcomes.

Set the experimentation standard. Establish frameworks for test design, guardrails, decision rules, and interpretation that improve both speed and rigor across teams.

Develop evaluation systems for complex products. For areas like matching, ranking, or applied AI experiences, build measurement approaches that combine offline evaluation, online experiments, and human-quality signals when needed.

Build scalable analytical assets. Invest in durable measurement systems: semantic definitions, self-serve dashboards, monitoring and alerts, and repeatable templates that reduce ad hoc work.

Mentor and uplevel. Coach other data scientists and analytics partners, provide strong technical review, and model what great looks like.

Be a thought leader. Proactively identify opportunities, shape roadmaps with an evidence-based POV, and create clarity where teams feel stuck.

What will make you successful

10+ years using data to drive product or business decisions in product, growth, engineering, or operations environments (or equivalent depth of experience and scope).

Expert fluency in SQL and strong proficiency in Python or R, including building reliable, reusable analysis workflows.

Deep expertise in Bayesian experimentation, causal inference, and measurement design, including common failure modes and how to prevent them.

Strong applied modeling judgment: you know when a model is the right tool, and you can build, validate, and launch responsibly.

Fluency with AI tools as part of your workflow, and a point of view on how data scientists on your team should use them: where they speed up analysis and prototyping, and where human judgment and rigor still have to lead.

A track record of leading ambiguous, cross-team work and delivering measurable outcomes (not just insights).

Excellent executive communication and influence: you earn trust, align stakeholders, and move decisions forward.

Strong product sense and an instinct for decision leverage: you focus on what changes outcomes, not what is merely interesting.

Motivation for our mission: improving access and affordability in mental healthcare.

Where you could land

Data Science at Headway is structured around three core pillars, each focused on a distinct area of the business. Within each pillar, smaller pods own specific problem spaces, and several of those pods are actively hiring. We keep our interview process consistent across teams, and ahead of your preliminary call we’ll share a pre-read with details on the specific pods that are hiring so we can talk through where you might fit best.

Patient: The Patient group owns how someone finds mental health care on Headway and gets to a provider who fits them: the first visit or phone call, search and matching, booking, and then attending a first appointment and staying in care. Data Science here means consumer funnel analytics, experimentation, and marketing science. That includes defining the metrics the group steers by, designing and reading experiments, and building causal and attribution methods for channels where you can't cleanly randomize. The modeling work spans ranking, matching, propensity, and the lifetime value and attribution models behind how we spend to acquire patients.

Payer & Outcomes: The Payer & Outcomes group is responsible for driving best-in-class patient outcomes, building a trustworthy and safe provider network, and delivering value-based care with responsible costs relative to outcomes, both through product work across the company and by working directly with payers. On the Data Science side, there's room to go deep on product data science, commercial data science, or a mix of both: experimentation, causal modeling, forecasting, and sizing work. People are often drawn to this team by its rapid growth and by how directly the day-to-day work ties back to Headway's mission.

Provider: Providers have real choices about where they build their practice. A provider might join Headway for credentialing, stay for reliable payments and tools that make the day easier, find new clients or bring over existing ones, or grow into a group practice. The Provider group owns that relationship and the trust it depends on, because we believe a clinician who feels supported can better help their patients. Data Science here is about understanding those choices: what draws a provider in, what keeps them, and what helps them grow with us.

Compensation and Benefits:

The expected base pay range for this position is $225,000-$265,000, based on a variety of factors including qualifications, experience, and geographic location. In addition to base salary, this role may be eligible for an equity grant, depending on the position and level.

We are committed to offering a comprehensive and competitive total rewards package, including robust health and wellness benefits, retirement savings, and meaningful ownership opportunities through equity. Compensation decisions are made holistically, ensuring fairness and alignment with market benchmarks while recognizing individual contributions and potential.

Benefits offered include:

Equity compensation

Medical, Dental, and Vision coverage

HSA / FSA

401K

Work-from-Home Stipend

Therapy Reimbursement

16-week parental leave for eligible employees

Carrot Fertility annual reimbursement and membership

13 paid holidays each year as well as a Holiday Break during the week between December 25th and December 31st

Flexible PTO

Employee Assistance Program (EAP)

Training and professional development

We believe a team's strength is in its people, and we cannot achieve this mission without a team that reflects the diversity of this problem – across race, ethnici