Product Manager, Meltwater

• 4 years+ in Product Management working with data-heavy systems - for example, data platforms, ML/NLP enrichment systems, or large-scale information architectures
• Customer value mindset: You understand how foundational data capabilities power end-user workflows, and you work closely with customer-facing PMs to translate platform capabilities into meaningful product improvements and outcomes
• Comfort working across teams: You collaborate confidently with engineering, data science, and other product teams
• Structured thinking: You enjoy making sense of complex data and building clear frameworks instead of isolated features
• Excellent communication skills: You can effectively translate data structure concepts into tangible product value for both internal and external stakeholders
• Strong technical understanding of structured data, APIs, and data modeling (you can converse comfortably with engineers and data scientists)
• Experience working with entity models or structured data relationships (e.g., knowledge graphs, taxonomies, or similar systems) and how they help with search, discovery, or interpretation of information

Desirable

• We’re looking for a Product Manager to lead the evolution of our core data foundation — the structured layer that connects and contextualizes information across Meltwater’s ecosystem
• You’ll shape and expand the semantic models that ensure key entities (such as organizations, channels, themes, etc.) are consistently identified and linked across our products
• Your work will enable more meaningful insights, better discovery, and clearer understanding for our users by making data relationships transparent, reliable, and easy to work with
• This role sits at the intersection of data architecture, enrichment, and product experience, translating complex data structures into intuitive, high-value capabilities for customers
• You'll own and evolve the core entity data model that connects key entities across our products (e.g., organizations, sources, themes)
• Unify and standardize datasets to reduce duplication and improve consistency and data reliability
• Define how entities are identified, matched, and maintained, combining automated methods with human review where needed
• Work closely with AI & Enrichment teams to ensure entity context improves classification, sentiment, topics, and narrative understanding
• Collaborate with Search & Retrieval teams to ensure fast, reliable entity-aware search and filtering experiences
• Set and monitor data quality measures, and drive ongoing improvements in accuracy, coverage, and consistency