Staff Data Scientist

About Us

Hungryroot is using AI to build the most consumer-centric food and wellness company to ever exist. We act as your personal assistant for healthy living—getting to know your goals, lifestyle, and budget, and recommending and delivering healthy groceries, easy recipes, and essential supplements for you and your family.

It’s the easiest way to eat healthy, achieve your goals, save time, and discover new foods. We believe food is the foundation of health, convenience should not mean compromise, and that everyone is unique in how they eat and live. That’s why we’re building a future in which healthy living is both easy and enjoyable.

Hungryroot is a distributed team of top talent across 28+ U.S. states. While we have a headquarters in New York City, our remote-first culture emphasizes collaboration, team-building, and flexibility. Expect regular virtual team events, strong ownership and accountability, and an annual company retreat.

We are looking for a Staff Data Scientist (Machine Learning)  to be a part of our growing Data Science team. You will be responsible for building and managing machine learning models to enhance personalization, optimize inventory, and streamline logistics.  You will be a key leader in our team, leading best technical practices, and driving ML strategy.

This role involves collaborating with various teams to translate business requirements into scalable machine learning solutions and owning the entire ML pipeline; from data exploration to model deployment, while staying up to date with industry advancements to apply innovative techniques effectively.

• Build, deploy, and maintain end-to-end machine learning models (decision trees, Bayesian models, clustering, for example) to drive personalization, recommendations, inventory optimization, and logistics
• Lead and evolve the ML function to support the next phase of Hungryroot’s Data Science team
• Collaborate cross-functionally with product, engineering, and ops to translate business needs into scalable ML solutions
• Ideate and brainstorm with Operations Research Engineers, ML Engineers, Data Engineers, and Data Analysts to continually enhance and drive the ML roadmap forward
• Own the full ML pipeline: from data exploration and feature engineering to model training, evaluation, and productionization
• Write clean, production-ready code with an emphasis on reusability, performance, and reliability
• Stay current with the latest trends and techniques in machine learning and apply them pragmatically to real-world problems

• 7+ years of hands-on experience in data science or machine learning engineering
• Strong foundation in statistical modeling, classical ML algorithms, and predictive modeling
• Demonstrated ability to technically lead a diverse group of data scientists, engineers, and analysts.
• Proficiency in Python, C++, and ML libraries (e.g.,pandas, NumPy, XGBoost, LightGBM).
• Experience with building, deploying, and maintaining models end-to-end in production environments
• Comfortable pair programming and working collaboratively in remote team environments
• Clear communication across technical levels and comfort working with diverse peers 
• Familiarity with Databricks and Spark
• Bonus: Experience in e-commerce, grocery, or subscription-based B2C models

• Remote-first: work from home, work from our NYC office, work from anywhere in the U.S. - you decide!
• Equity 
• Unlimited vacation policy
• Universal paid parental leave
• Monthly Hungryroot credit for delicious, healthy groceries
• Comprehensive health, vision, dental, and life insurance
• 401k with Company Match
• A work from home stipend to support your initial home-office setup

Expected Pay Range$185,000 - $215,000

#LI-REMOTE

The employer will not sponsor applicants for work visas.

Our mission to help make healthy eating easy, accessible, and joyful is better served by a diverse workplace. We are a proud Equal Opportunity Employer committed to building an inclusive workplace. We have zero-tolerance for harassment or discrimination. We do not discriminate on the basis of any protected class.