About this role
Professionals who thrive on tackling hard, ambiguous problems and running toward unglamorous work will find a fitting challenge at Nourish. The team builds an AI-native digital health system that matches patients with registered dietitians, physicians, and AI agents to deliver insurance-covered care across the country. Operating as the Lead Data Scientist embedded within the Product team, you will own analytics for a business-critical function by developing a deep understanding of patient needs and translating insights into strategic opportunities.
This position exists to leverage data as a primary driver of growth and patient outcomes in a rapidly scaling metabolic health clinic. The scope of work blends product analytics, experimentation, and predictive modeling in a marketplace environment where you will build production-ready models and apply causal inference methods. An ideal candidate brings high resilience without ego, values candid feedback, and combines deep technical execution with strategic product partnership to shape company roadmaps.
What you will do
- Define core metrics and surface insights to shape business understanding and inform the product roadmap.
- Build, validate, and maintain production-ready predictive models for churn, resurrection, and targeting.
- Deliver high-impact analyses by breaking down complex topics into clear narratives with sized business opportunities.
- Design and analyze experiments while applying causal inference methods to measure the impact of features and adoption where experiments are not feasible.
- Partner closely with Product teams to work backwards from problem sizing and propose actionable roadmap priorities.
- Contribute to the development of company-wide experimentation platforms, methodologies, standards, and tooling.
What you need
- Bring 6 or more years of relevant experience owning data science or product analytics, ideally within a consumer tech company or a marketplace.
- Demonstrate expertise in experimentation end-to-end and apply causal inference methods when traditional experiments are not feasible.
- Write clean, performant SQL and show proficiency in Python for technical data tasks.
- Exhibit curiosity, strategic thinking, and outcome-orientation by proactively framing the right questions and balancing speed with depth.
- Communicate complex ideas clearly by distilling deep analyses into crisp takeaways that earn trust across cross-functional teams.
- Share a strong motivation for the company mission to use food as medicine and improve lives at scale.
Skills and tech stack
Questions candidates ask
What is the work setup for this data science role?
The data team is based in New York City and goes into the office 2 to 3 days a week. While a specific number of office days is not strictly required, the team looks for individuals willing to join onsite.
What core technical skills are required for the position?
Candidates must be able to write clean, performant SQL and demonstrate proficiency in Python. Additionally, expertise in experimentation and causal inference methods is essential.
What types of predictive models will the lead data scientist build?
You will build, validate, and maintain production-ready predictive models that focus specifically on churn, resurrection, and targeting.