Senior Staff Data Scientist - Bayesian Experimentation & Causal Inference

Overview

Headway’s mission is to build a new mental healthcare system that everyone can access. We automate administrative tasks for therapists and provide tools to manage their practices. Over 75,000 providers and 1 million patients use our software. We are a Series D company with $325M+ in funding, seeking exceptional people to help achieve our mission.

Responsibilities

• Own causal inference and experimentation standards across Headway
• Define canonical approaches, guardrails, documentation, and review mechanisms for experiments and quasi-experiments, including when and how to use Bayesian methods
• Create a clear, shared framework for mapping findings to levels of confidence
• Operationalize the confidence ladder so it shows up in artifacts teams actually use
• Tackle difficult measurement problems like interference and spillovers, network effects, selection bias, noncompliance, measurement error, multiple comparisons, seasonality, and Simpson’s paradox
• Partner with Data Platform and Engineering to make rigor scalable
• Mentor and set the bar for other data scientists and analytics leaders

Requirements

• 12+ years of experience applying causal inference, experimentation, and advanced statistics to real-world product, growth, or operational decisions
• Deep expertise in causal inference across randomized and observational settings
• Strong SQL and proficiency in Python or R, including building reusable analysis tools and improving team workflows
• Executive-level communication and influence: drive alignment across Product, Growth, Ops, Finance, and Engineering
• Comfort operating in ambiguity and turning it into crisp frameworks, clear recommendations, and measurable outcomes
• Motivation for improving access and affordability in mental healthcare

Qualifications

• Track record of setting org-wide standards that materially improved decision quality and execution velocity
• Experience in marketplaces, healthcare, insurance, or other regulated and complex incentive systems (nice to have)
• Experience with experimentation under interference and network effects (nice to have)
• Experience building experimentation platforms, analysis libraries, or statistical tooling used broadly across an organization (nice to have)
• Familiarity with causal graphs, uplift modeling, and decision theory framing (expected value, value of information) (nice to have)

Benefits

• Compensation range: $249,600 - $312,000
• Benefits: Medical, Dental, Vision coverage, HSA / FSA, 401K, Work-from-Home Stipend, Therapy Reimbursement, Carrot Fertility annual reimbursement and membership, 13 paid holidays, EAP, Training and professional development