Description
Join us to build the decision engine for better mental health outcomes.
As a Senior Data Scientist, you will sit in the heart of a cross-functional product team and help turn messy, real-world signals into clear decisions. You will make sure we are capturing the right data, designing experiments that tell us what is actually driving outcomes, and translating findings into recommendations that teams can act on quickly.
When the insight is stable and valuable, you will help operationalize it through predictive models that improve provider and patient experiences.
Key responsibilities include:
- Being the analytics partner inside the pod, working closely with Product, Engineering, Design, Ops, and Clinical stakeholders to define questions, metrics, guardrails, and decision rules.
- Running rigorous experiments, designing and analyzing A/B tests and quasi-experiments with clear hypotheses, power considerations, and pre-defined success criteria.
- Connecting behavior to strategy, using funnel, cohort, segmentation, and lifecycle analysis to understand how people and providers experience Headway, and where product changes will have the biggest impact.
- Using causal inference when experiments are not possible, applying approaches like diff-in-diff, matching, and regression-based designs with principled uncertainty quantification.
- Building models when they should exist, developing predictive models that operationalize vetted insights (feature development, validation, backtesting, calibration), with clear launch criteria and monitoring plans.
- Creating decision-ready work, producing analysis and narratives that are crisp, honest about uncertainty, and drive action.
To be successful in this role, you will need:
- 6+ years using data to drive product or business decisions in product, growth, engineering, or operations environments.
- Strong SQL and strong proficiency in Python or R for analysis and modeling.
- Demonstrated depth in experimentation and causal inference under real-world constraints.
- Practical modeling skill: feature engineering, model comparison, cross-validation or backtesting, calibration, and post-launch monitoring.
- Strong product sense and opinions, including a track record of connecting analytics recommendations to measurable outcomes.
- Clear communication: you can explain complex work to non-technical audiences without losing the truth.
- A self-starter mindset: you prioritize well, follow through, and do not need heavy oversight.
- Motivation for our mission: improving access and affordability in mental healthcare.
The expected base pay range for this position is $180,000 - $225,000, 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.