Principal Product Manager – High Volume Lifecycle

Company: Wise
Apply for the Principal Product Manager – High Volume Lifecycle
Location: London
Job Description:

Overview

As Product Manager for High Volume servicing, you own the end-to-end servicing experience for our most active customers, ensuring expert, personalised support at scale. You will drive cross-functional initiatives with Operations, Fincrime, Compliance, and Design to improve activation, retention and satisfaction for high-value users. You’ll blend data, design thinking and AI-enabled solutions to make servicing more predictive and efficient, while keeping compliance and scalability at the forefront. This role offers the chance to shape how Wise supports a critical revenue-driving customer segment and to lead impactful, cross-team initiatives.

Pay / Benefits

  • RSUs
  • Wise Benefits

Responsibilities

  • Shape vision, strategy and roadmap for the High Volume servicing area and align with broader HV goals
  • Own the HV servicing experience to ensure premium treatment and consistent outcomes
  • Scale operational capabilities and deploy AI solutions where they add value for customers
  • Increase predictability and confidence for customers transacting at scale
  • Collaborate with Send, Operations, Contacts, Fincrime and Compliance to balance growth with controls and regulatory requirements
  • Work across HV servicing with cross-functional teams to align with business goals and platform capabilities

Key requirements

  • Strategic depth to convert ambiguity into actionable strategy
  • Strong service design sense with a focus on frictionless, predictable customer interactions
  • Ability to influence without formal authority across Operations, Servicing, Fincrime and other PMs
  • Strong data skills, including SQL, to inform decisions and tell a future-of-HV servicing story
  • Enjoy solving hard problems and leveraging servicing as a growth lever
  • Strategic thinking
  • Influence without authority
  • Cross-functional collaboration
  • SQL and data-driven decision making
  • Data storytelling and hypothesis testing
  • AI solution deployment where appropriate

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Posted: October 1st, 2026