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dunnhumby

Global customer data science and insights

Product Manager

Product ManagementPosted on Nov 5
Full-timeLondon, UKNo salary listed

About the Job

Requirements

  • Proven Product Management experience delivering complex, data-led products across the product lifecycle, including hands-on research and discovery.
  • A strong analytical mindset, with experience working with data science, analytics, or insights-driven products and an interest in how data can solve customer problems.
  • Technical understanding of APIs, ideally with experience delivering products or services that use APIs to make data or models scalable and accessible.
  • Strong stakeholder and client management skills, with the ability to communicate clearly, facilitate discovery, and bring different teams together around a shared product vision.
  • Experience working in agile product environments, including managing roadmaps, prioritising backlogs, and partnering closely with engineering or technical teams.

Responsibilities

  • Own the end-to-end product lifecycle, including research, discovery, delivery, measurement, and continuous optimisation.
  • Define and execute product strategy, roadmaps, and backlog priorities, ensuring the squad has clarity on the problems and opportunities that matter most.
  • Partner closely with data science, engineering, and analytics teams to deliver scalable solutions, including data science models that are API-ready.
  • Build a deep understanding of Tesco’s users and stakeholders, translating customer and commercial needs into clear product requirements, user stories, and outcomes.
  • Establish measures of product success and use data, experimentation, and customer feedback to inform decisions and continuously improve the product.

About the Company

dunnhumby

Global customer data science and insights

Dunnhumby uses Customer Data Science to help retailers and consumer brands improve customer experiences through data-driven insights, offering services like media solutions, customer insights, and personalized marketing strategies, and it also runs Dunnhumby Ventures to back early-stage retail tech startups. It analyzes shopper data from browsers and internet devices using unique identifiers without storing personal information to generate actionable insights that drive targeted campaigns. It differentiates itself by combining depth in retail-focused data science with a suite of services and a corporate venture fund to help clients optimize customer interactions across channels. Its goal is to empower retailers and brands to deliver better, data-informed experiences that boost sales and engagement.

Company size
1,001-5,000
Company stage
Acquired
Total funding
Not listed
Headquarters
London, United Kingdom
Founded
1989

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