Staff Data Scientist
- Location
- New York, NY
- Job type
- Full-time
- Level
- Lead / Staff
- Experience
- 6+ years
- Listed
- 23 days ago
Skills & highlights for this role
- experimentation
- causal inference
- SQL
- Python
About the Role
We're scaling quickly, and data is one of our most important strategic levers for unlocking growth and improving patient outcomes. As a Staff Data Scientist, you'll embed with our Product team and own analytics for a specific, business-critical function-developing a deep understanding of our patients and their needs and turning that understanding into business opportunities.
This role blends product analytics, experimentation, and predictive modeling in a marketplace setting: you'll build and validate production-ready models, use causal inference to isolate the impact of features and feature adoption, and produce deep dives that end in clear recommendations with sized business opportunities. You'll also contribute to the development of our experimentation platform, and collaborate closely across our Product, Engineering, Design & Growth teams.
Our data team is based in NYC and goes into the office 2-3 days a week. While we don't require a specific number of days in office, we're looking for people who would be excited to join us onsite.
Key Responsibilities
- Own data and analytics end-to-end: Define the metrics and surface the insights that shape our understanding of our business and inform the product roadmap
- Develop production-ready predictive models: Build, validate, and maintain models of churn, resurrection, and targeting
- Deliver high-impact analyses: Break down complex topics into clear narratives and recommendations with sized business opportunities
- Drive scientific decision-making: Design and analyze experiments, and where experiments aren't feasible, apply causal inference methods to measure the impact of features and feature adoption
- Be a thought partner to Product: Work backwards from sizing a problem to proposing what we should do about it, and shape team priorities and roadmaps
- Contribute to our experimentation platform: Help build the methodology, standards, and tooling that teams across the company rely on
We'd Love to Hear From You If You
- Have 6+ years of relevant experience: You've owned data science or product analytics for a product area, ideally at a consumer tech company or a marketplace
- Are an experimentation and causal inference expert: You've designed and analyzed experiments end-to-end, and applied causal inference methods where experiments weren't feasible
- Bring strong technical skills: You write clean, performant SQL, and are proficient in Python
- Are curious, strategic, and outcome-oriented: You proactively shape the right questions, translate complex data into clear, actionable insights, and balance speed with depth to drive high-impact decisions
- Communicate complex ideas with clarity: You distill deep analysis into crisp, actionable takeaways, and you earn trust across cross-functional teams
- Are motivated by impact and mission: You believe in the power of food as medicine to transform healthcare and are excited to improve lives at scale by contributing to Nourish's mission
More Information
The Nourish Bar
About Us
Health is the most important thing in life, and the American healthcare system is completely broken - poor outcomes, high cost, bad patient experience. We're building a new system from the ground up.
Our mission is to improve people's health by making it easy to live a healthy lifestyle.:
Nourish is the country's largest dietitian-led metabolic health clinic. We're an AI-native digital health system matching patients with 10,000+ Registered Dietitians, physicians, medications, lab testing, and AI agents to deliver insurance-covered care across all 50 states. Founded four years ago, we've completed millions of appointments, tripled year-over-year, and partnered with health plans covering 200M+ Americans across 250+ health systems.
In 2026 we raised a $100M Series C, bringing total funding to $215M. The round was led by Menlo Ventures, with participation from Thrive Capital, Index Ventures, J.P. Morgan Growth Equity Partners, Maverick Ventures, Y Combinator, BoxGroup, Atomico, Daybreak, and Operator Partners.
Learn more about our Series C here: Nourish Blog, Bloomberg, Fierce Healthcare, Digital Native, The Pulse Podcast.
This is not a job for everyone. We hold an extremely high bar because we believe talent density is our biggest competitive advantage. We're looking for people who actively choose hard, ambiguous problems, who run toward unglamorous work, give and receive candid feedback, and bring relentless resilience without the ego. Our work is important, but we are not self-important. We do this because we're solving one of the hardest problems in the world, and the problem matters. If that's you, we disproportionately reward it.
Our Values
- Why Nourish Exists
- How We Work
- Comp Philosophy
Benefits
From Nourish's careers page, first listed on Rolev.ai on October 17, 2026. Rolev.ai is not the employer.
How Rolev.ai helps with this application
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Common questions
Where is the Staff Data Scientist job at Nourish located?
This Staff Data Scientist position at Nourish is located in New York, NY. Always check Nourish's application page for specific state eligibility or relocation policies.
What qualifications are required for Staff Data Scientist at Nourish?
For the Staff Data Scientist role, Nourish highlights 6+ years of relevant experience; experience with experimentation, causal inference, SQL, Python. Rolev.ai can score your existing resume against these requirements and show any skill gaps before you apply.
How do I apply for the Staff Data Scientist position at Nourish?
This listing links directly to Nourish's Greenhouse application page. You can apply directly on Nourish's site, or use Rolev.ai to check your resume fit, generate a zero-hallucination tailored resume and cover letter for this posting, and autofill the Greenhouse application form in 1 click with the Rolev.ai Chrome extension. You always review the form and press Submit yourself.