Note: The job is a remote job and is open to candidates in USA. Hungryroot is using AI to build a consumer-centric food and wellness company. They are seeking a Senior Data Scientist to lead machine learning initiatives that enhance customer personalization and improve engagement through data-driven insights.
Responsibilities
- Separate durable preference from noise. Design robust feature representations from high-cardinality, implicit behavioral data (swaps, skips, saves) to capture true user intent and predict future engagement
- Model temporal dynamics and changing tastes. Architect sequential and recency-aware systems that adapt to shifting user preferences, ensuring recommendations reflect current intent rather than stale history
- Solve the cold-start problem. Leverage cohort signals, clustering, and content embeddings to generalize learnings across users, ensuring that even a new customer’s first box feels deeply personalized
- Bridge ML and constrained optimization. Integrate model scores (e.g., predicted conversion) with operations-research engines to perform business-aware re-ranking, balancing personalization with hard constraints like diet, budget, and inventory
- Advance the modeling. Evolve our systems using the architectures that drive modern, high-scale personalization, such as multi-stage retrieval and ranking, learning-to-rank (LTR), matrix factorization, and gradient-boosted trees. You will also evaluate and integrate more sophisticated techniques (like contextual bandits or sequence modeling) as our data complexity grows
- Drive rigorous experimentation. Define robust offline evaluation metrics (e.g., NDCG, MAP) and design online A/B tests to measure true causal impact on customer retention and satisfaction
Skills
- 5+ years of hands-on experience in data science, applied machine learning, or a related quantitative role
- Champion ML system best practices. You treat the ML lifecycle as a rigorous discipline, moving systematically from problem definition and feature engineering to robust offline evaluation, online experimentation, and CI/CD for ML
- Deep expertise in personalization, search ranking, or recommender systems, with hands-on experience building multi-stage architectures (candidate generation, scoring, and re-ranking)
- Strong grounding in statistics, causal inference, and experimentation, with the ability to define proxy metrics and design tests that measure long-term business impact
- Production-level engineering skills in Python and SQL, with hands-on experience scaling models using big data frameworks and an understanding of system latency trade-offs
- A commercial mindset to translate complex business constraints into scalable ML architectures
- Clear communication and a collaborative, remote-friendly working style, including mentoring others
- Experience with deep learning frameworks (e.g., PyTorch, JAX) for representation learning, embeddings, or sequence modeling
- Probabilistic or hierarchical (Bayesian) modeling
- Mathematical optimization or operations research (e.g., Mixed Integer Programming, Gurobi)
- Reinforcement learning or contextual bandits for explore-exploit trade-offs
- Experience in e-commerce, grocery, or subscription-based B2C
Benefits
- 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
Company Overview