Senior Product Manager, Personalization

Role Overview

Senior Product Manager, Personalization to lead the product vision, strategy, and execution for next-gen personalization systems. You’ll own the personalization engine across the full eater journey, working closely with ML, engineering, data science, design, and culinary teams.

Responsibilities

• Define and drive product strategy for end-to-end personalization, including:
  • Recommendations and ranking algorithms
  • Adaptive feed and intent modeling
  • Predictive food preferences
• Build a unified personalization strategy across discovery, ordering, search, and post-order experiences.
• Translate customer insights and behavioral data into personalized ordering journeys for weekly menus.
• Ship high-impact personalization features by partnering with Engineering and ML on:
  • Personalized ranking and contextual suggestion surfaces
  • Food-intent clustering and dietary preference modeling
  • Personalization-aware UX
• Drive experimentation (A/B testing) and establish offline/online model evaluation to measure lift.
• Deeply understand customer behavior:
  • Early-week ordering signals, cuisine preferences, dietary constraints
  • Long-term engagement drivers
  • Identify behavioral segments/affinity clusters with Data Science
• Cross-functional leadership with:
  • Design (adaptive homepages, personalized filters, “you might love,” order-again flows)
  • Chefs and Culinary (menu diversity, cuisine metadata, ingredient-level signals)
  • Growth/CRM/Marketplace (personalize acquisition, onboarding, reactivation)
• Drive measurable business impact:
  • Improve CVR, add-to-cart rate, and search success rate
  • Lift retention, order frequency, and net AOV
  • Increase long-term revenue and reduce decision friction

Requirements

• Experience building ML-powered product experiences involving ranking, recommendations, or personalization platforms.
• Strong analytical skills with comfort in experimentation, model evaluation, and user behavior analytics.
• Ability to simplify complex technical problems into user-centric product solutions.
• Excitement about personalizing a large, dynamic food catalog into weekly experiences.
• Collaborative and decisive working style.

Nice-to-Haves

• Not explicitly stated beyond the listed expertise areas (ML, ranking/recommendations, personalization).