Senior Data Scientist

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Hungryroot

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2017

🛍️ eCommerce

🧘 Wellness

👥 B2C

eCommerce • Wellness • B2C

Hungryroot is a personalized, healthy food delivery service that focuses on making healthy eating accessible and convenient. The company offers tailored meal plans and easy-to-prepare recipes that cater to a variety of dietary preferences and goals, including gluten-free, vegetarian, high-protein, dairy-free, and more. Customers can save time on meal planning, shopping, and cooking, while reducing food waste and saving money. Hungryroot emphasizes fresh, whole foods and provides a wide range of meal options to support different nutritional needs. It aims to help customers achieve their health goals, such as reducing inflammation or increasing energy, with a flexible and budget-friendly subscription model.

📋 Description

• 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

🎯 Requirements

• 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.

🏖️ 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