Data Scientist
accenturefederalservices
Staff Data Scientist
usenourish· Analytics
About this role
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.
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 our 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, cuse 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
Frequently Asked Questions
Is the salary disclosed for the Staff Data Scientist position at usenourish?
The salary for this Staff Data Scientist role at usenourish is not publicly listed. Click "Apply Now" to learn more about the compensation package on their official careers page.
Where is the Staff Data Scientist position at usenourish located?
This Staff Data Scientist role at usenourish is based in New York, NY. The position is listed as on-site or hybrid. Check the full job description or apply directly to confirm the work arrangement.
Which team or department does the Staff Data Scientist at usenourish belong to?
This Staff Data Scientist position is part of the Analytics department at usenourish. See the full job description for more information about the team structure and responsibilities.
How do I apply for the Staff Data Scientist position at usenourish?
Click the "Apply Now" button on this page. You will be redirected to usenourish's official application portal hosted on greenhouse where you can submit your application directly.
When was the Staff Data Scientist job at usenourish posted?
This Staff Data Scientist position at usenourish was posted on Sep 22, 2026. Apply as soon as possible — early applications are often reviewed first.
Staff Data Scientist
usenourish
You'll be redirected to usenourish's official application page on Greenhouse.