Data Scientist: Product

Data Scientist: Product at ThatchThatch is changing how health benefits work. We're building software that makes it easier for businesses to offer health coverage and gives employees more choice and control. We're looking for a Data Scientist to help our Product and Operations teams understand how people use Thatch and where we can make the biggest impact. You'll own the data models and metrics behind our product, from plan shopping and enrollment to reimbursements and everyday benefit usage. You'll dig into user behavior, uncover friction, and design experiments that help us decide what to build and improve next. This is a hands-on role where you'll build the analytics foundation teams rely on, turn complex data into clear recommendations, and help shape our product strategy. Partner with Product and Operations to answer important questions and inform product priorities. Define and own product metrics, from company-wide success measures to feature-level performance. Analyze user journeys, engagement, and operational data to uncover friction and opportunities. Design and evaluate experiments to measure the impact of product changes. Build and maintain dbt models, metrics, dashboards, and analytical tools that teams rely on. Improve data quality, instrumentation, and self-serve analytics so teams can make confident decisions. Experience using analytics, data science, and experimentation to influence product decisions. Strong SQL skills and experience with dbt or similar data transformation tools. Experience building analytical data models and dashboards using BI or visualization tools. Proficiency in Python for analysis, experimentation, or statistical modeling. Strong product judgment and the ability to turn complex findings into clear, actionable recommendations. Comfortable working independently, navigating ambiguity, and partnering across teams. Data: Snowflake, SQL, dbt Analytics: Omni, Hex, Python Development: GitHub, CI/CDAI: Claude, ChatGPT, Copilot, and other tools that help us work faster and smarter You won't work directly in our application layer day-to-day, but familiarity with source data and event instrumentation from systems like Ruby on Rails is helpful. Influencing product roadmaps and prioritization through data. Building experimentation practices, including guardrail metrics, sample-size guidance, or analysis frameworks. Analyzing funnels, retention, cohorts, or engagement across complex user journeys. Building statistical or machine-learning models for segmentation, forecasting, propensity, or recommendations. Experience in healthcare, fintech, or other regulated industries. We aim to move quickly, and most candidates complete the process within 2–3 weeks. You can expect: An initial conversation with a recruiter. A conversation with the hiring manager and a lightweight Python coding exercise. A take-home analytics exercise. A review of your work, a data modeling and metrics exercise with the team, and a discussion with cross-functional partners. A final conversation with engineering and company leadership.