Principal Product Manager - Discovery and Personalisation

As our journalism spans an ever-growing archive and range of formats, helping audiences find, explore and understand our content within our products is central to delivering long-term value. Search and discovery are not simply navigational utilities, but core expressions of how our journalism is structured, explained and trusted. 

We are seeking an experienced and highly capable Principal Product Manager to lead Search & Discovery across The Economist’s web and app products. This role brings together responsibility for how users actively find content through search and how they browse, explore and build reading habits through discovery. 

This role is ideal for someone who is both strategic and hands-on - someone who can set a clear vision for a complex, editorially-grounded product area while also driving measurable improvements to engagement, satisfaction and long-term subscriber value. 

The role 

The Principal Product Manager for Discovery & Personalisation will own how subscribers find, explore and return to The Economist's journalism across web and app. This is a senior, cross-cutting role spanning two closely related disciplines:

Discovery. Owning the on-platform representation of our content - search, navigation, browse patterns and conversational interfaces that allow users to interrogate the archive and find authoritative journalism efficiently. This includes keyword and semantic search, ranking and surfacing logic, and generative AI features such as Q&A, content summarisation and conversational discovery experiences. A key part of this work is establishing the evaluation frameworks and human-in-the-loop processes that ensure AI-powered features are grounded in user trust and consistent with our editorial brand.       

Personalisation. Owning the recommendation and ranking algorithms that drive browse-led experiences — helping subscribers decide what to read, watch or listen to next. This means defining the behavioural signals and contextual inputs that feed personalisation models, partnering with data science on model development and evaluation, and ensuring our systems support habit formation without narrowing editorial perspective.

The role interfaces with Web, App, Data science, Editorial and Analytics teams.

• Own the vision and roadmap for Discovery & Personalisation across web and app.
• Lead the evolution of keyword and semantic search, including relevance, ranking and result quality.
• Own browse-led personalisation systems — defining the signals, models and decisioning logic that surface relevant, timely content for individual subscribers.
• Lead the creation of generative AI features including Q&A, content summarisation, explainer and conversational discovery experiences that help users explore and connect our journalism.
• Establish robust evaluation frameworks and human-in-the-loop processes to ensure AI-powered features are accurate, transparent and aligned with our editorial values.
• Partner closely with data science on the definition, evaluation and iteration of ranking and recommendation models.
• Maintain strong judgement around responsible, transparent and editorially-aligned personalisation — preserving journalistic breadth and integrity.
• Work closely with Editorial to ensure discovery and personalisation reflect journalistic judgement and trust, and that the right feedback loops are in place.
• Collaborate with Web and App teams to ensure consistent, high-quality implementation of discovery and personalisation experiences across platforms.
• Define and track success metrics related to findability, relevance, engagement, habit formation and trust.
• Communicate strategy, priorities and performance clearly to senior stakeholders across product, editorial and technology.

• Builder: You have owned and shipped complex search, discovery, recommendation or personalisation systems in content-rich or subscription products.
• AI-fluent: You have hands-on experience defining and evaluating generative AI features — you understand the product, trust and editorial considerations that make AI experiences succeed or fail.
• Data-informed: Comfortable working with data scientists on ML-driven systems, evaluation frameworks and experimentation.
• Product-led: Strong judgement in defining strategy, translating it into roadmaps, and delivering outcomes through cross-functional teams in lean environments.
• Editorially-aware: Confident balancing user intent, algorithmic optimisation and editorial integrity.
• Communicator: Able to explain complex systems and trade-offs clearly to both technical and non-technical audiences.
• Collaborative: Comfortable learning, iterating and working across disciplines — engineering, data science, design and editorial — in a fast-moving environment.

• Search and discovery systems, including semantic retrieval, ranking and evaluation.
• Personalisation systems, behavioural signals and experimentation.
• Generative AI product development and conversational interface best practices.
• Responsible AI, algorithmic transparency and human-in-the-loop design.
• Metrics for discovery quality, relevance, user understanding and trust.
• Subscription or habit-forming digital products.
• Multi-format digital content environments.
• Enthusiasm for The Economist's mission, journalism and global audience.

#LI-Hybrid