Senior Product Manager responsible for Centific’s LLM post - training and evaluation strategy. Leading product roadmaps and cross - functional teams in AI advancements.
About the role
- Product Manager specializing in data and analytics capabilities at TomTom. Collaborating with cross-functional teams to shape data-driven product strategies in Amsterdam.
Responsibilities
- Own the vision, strategy, and roadmap for data & analytics capabilities that enable product teams to be truly data-driven and product-led
- Lead the end-to-end product lifecycle—from discovery and scoping through development, rollout, and continuous improvement
- Drive cross-team alignment and stakeholder buy-in across engineering, data science, and business teams
- Advance trusted metrics and governance: shape frameworks for metric definitions, quality, monitoring, and alerting
- Evolve our data architecture—helping move toward data mesh-inspired models (decentralized ownership, federated governance) while balancing centralized needs
- Contribute to key technical decisions—you’re fluent discussing data storage, APIs, event schemas, and analytics/ML needs with engineers and data scientists
- Champion operational excellence—embed data quality practices, efficient pipelines, access controls, and compliance guardrails into daily work
- Evangelize and educate: help build a data-driven culture through playbooks, enablement, and training
Requirements
- 5+ years in Product Management (or similar roles building data platforms/products), delivering outcomes with cross-functional teams
- Technical depth: comfortable with data architectures and analytics workloads; able to discuss schemas, telemetry, storage options (warehouses/lakes), APIs, and experimentation frameworks
- Experience with data mesh or similar decentralized data ownership/governance models, or migrating from silos to hybrid approaches
- Proven ability to set vision/OKRs, make clear product decisions amid ambiguity, and align multiple stakeholder groups
- Track record improving metrics quality and trustworthiness (definitions, monitoring, anomaly detection, freshness/latency) and enabling self-service analytics at scale
- Exposure to AI/ML enablement for product teams (agent-assisted analytics, analytics stores optimized for LLMs, vector search, etc.)
- Experience shaping data governance & access control across multiple systems with varying sensitivity levels
Job title
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