Product Manager - III (personalization & Ai)

Expedia Expedia · Hospitality · Gurgaon, India

Product Manager III to own and drive the personalization and AI-powered checkout transformation, combining predictive personalization with real-time interventions to convert checkout from a friction point into a conversion engine.

What you'd actually do

  1. Define and execute product strategies and roadmaps for checkout personalization and AI-driven interventions, using data and experimentation to drive prioritization and decision-making across predictive and adaptive personalization domains.
  2. Translate customer, partner, and business needs into clear problem statements, detailed requirements, and acceptance criteria — delivering high-quality product specifications, including API contracts, P13N signal integrations, and data needs to engineering teams.
  3. Collaborate closely with engineering, design, data science, and stakeholder teams to drive end-to-end delivery of personalization features and AI-powered interventions, ensuring scalable system design, reliable integrations, and strong operational performance.
  4. Use quantitative and qualitative insights to monitor product performance, continuously iterate on features, and manage trade-offs across usability, performance, technical constraints, and business impact — with a focus on conversion, abandonment recovery, and traveler confidence.
  5. Safely integrate and operate AI/ML-enabled, data-driven product capabilities that improve traveler outcomes — including predictive models for abandonment risk, and propensity-based personalization — in partnership with data science and engineering teams.

Skills

Required

  • Product management experience
  • Define product requirements
  • Write user stories or PRDs
  • Interpret data and metrics
  • Use experimentation or A/B testing
  • Collaborate with engineering on system behavior, API-level requirements, data flows, and dependencies
  • Familiarity with AI-driven systems, tools, or workflows
  • Applying AI/ML concepts to real-world products

Nice to have

  • Experience taking products from concept to scaled adoption
  • Defining success metrics
  • Validating problem-solution fit
  • Managing iterative releases at scale
  • Personalization, conversion optimization, or checkout/funnel domains
  • Leading product strategy in complex technical environments
  • Partnering with engineering on system design, integration patterns, and operational readiness
  • Driving measurable impact using data, experimentation, and customer insights
  • Working with analytics, experimentation platforms, and instrumentation requirements
  • Influencing cross-functional and cross-organizational stakeholders
  • Resolving conflicting priorities
  • Driving alignment on roadmaps and trade-offs
  • Experience leveraging AI productivity tools (Cursor, Claude, Figma AI)
  • Experience with low-code agent platforms (Alloy, n8n)

What the JD emphasized

  • AI-driven interventions
  • predictive personalization
  • AI/ML-enabled
  • data-driven product capabilities
  • predictive models
  • propensity-based personalization
  • AI/ML concepts

Other signals

  • personalization
  • AI-driven interventions
  • predictive models
  • traveler outcomes