Hive's enrichment products bring Hive intelligence to wherever customers and partners work. This spans:
- Geographic scores and segments, from hyperlocal to national
- Audience and segment enrichment
- Enhancement of customers' data
- Model-based attributes
- Datasets licensed through marketplaces and clean rooms
- Outputs ready for use in media and marketing platforms
You'll be responsible for strategy through delivery, leading a squad building & delivering product to some of the biggest brands, agencies and software partners in the world.
What you'll do
- Own the product strategy, roadmap and priorities for Hive's enrichment products and external data ecosystem.
- Lead ongoing efforts to scale Hive intelligence that can be joined, enriched, licensed, delivered and activated across partner and customer environments.
- Develop deep knowledge of the competitive ecosystem, including data providers, data marketplaces, clean rooms, audience platforms, geodemographic and segmentation providers, research platforms and activation environments.
- Translate customer, partner and commercial opportunities into clear product requirements, technical priorities and sequencing decisions for the squad.
- Maintain a rigorous view of the difference between a one-off customer integration and a capability worth building into the platform.
- Drive the squad toward reusable capabilities that make each new dataset, partner and activation environment faster and cheaper to support.
- Balance short-term revenue opportunities with the foundational architecture a durable enrichment business requires.
- Define success metrics spanning coverage, statistical quality, latency, implementation time, reliability, usability, adoption and commercial value.
- Work deeply enough with the science to understand differences in model validity, coverage and uncertainty across products and grains, and deeply enough with engineering to understand architectural tradeoffs.
- Make smart product decisions when scientific quality, engineering complexity, customer requirements and speed to market are in tension.
- Write clear product requirements and acceptance criteria while giving engineers and scientists room to determine the best technical solution.
- Own and continuously prioritize the squad backlog around business outcomes rather than output volume.
- Identify opportunities to extend Hive intelligence through new data partners, marketplaces, platforms, customer datasets and activation environments.
- Work closely with commercial and partnership teams to understand what stops a customer from saying yes, whether the barrier is coverage, integration, methodology, delivery mechanism, procurement or packaging.
- Track where the data market is moving, including privacy-safe data collaboration, clean rooms, AI-enabled enrichment, synthetic and model-based attributes, first-party data enhancement and interoperable data products.
- Keep engineering, science, commercial and leadership aligned on what we're building, why it matters and what winning looks like.
