Full Job Description
You9ll own one of IV.AI9s core data product lines end to end, spanning consumer panel data and web intelligence capture, for blue-chip clients. Your job is turning raw data acquisition into reliable, client-ready insight products. You don9t just write requirements and hand them off; you read the data yourself, dig into anomalies, and act as a credible technical counterpart to engineering on schema and pipeline decisions.
What you9ll own (and how we measure it)
Product line ownership
3 Own the roadmap and day-to-day product decisions for your data product line end to end, from data acquisition/capture through data quality to the client-facing insights blue-chip clients depend on.
3 Be involved in the full product lifecycle, from problem definition through shipped, measured outcomes.
Data quality and technical depth
3 Treat data correctness as the top priority. Define what "good data" means for your product, partner directly with engineering on schema, pipeline design, and validation logic, and own the metrics that prove it9s working.
Growth and metrics
3 Drive growth within your product line. For panel-based products, this includes contributor/panelist acquisition, activation, and retention. For web intelligence, this includes source coverage and data freshness.
3 Instrument and monitor the metrics that matter for your product (funnel visibility, capture coverage, data delivery reliability) and use them to prioritize the roadmap.
Client-facing product and cross-functional alignment
3 Translate raw data capability into client-facing insight products. Write the specs, define the dashboards, and make the call on what ships.
3 Represent your product line in cross-functional planning, aligning with the other data product PM and engineering on shared data contracts and standards across product lines.
3 Run your roadmap, specs, sprints, and day-to-day execution through tools like Linear and Notion, keeping planning and documentation visible to the team.
3 Use AI tools as a core part of your own workflow, for research, drafting specs, data analysis, or prototyping, and look for real opportunities to build AI/NLP capability directly into the product itself.
The reality of this role
3 Small, distributed team: you9ll help build the roadmap and standards, you don9t inherit them fully formed.
3 You9ll work directly with engineers, not just hand off requirements.
What we9re looking for
Must-haves
3 Bachelor9s degree
3 4-6+ years of experience, including meaningful time in a Product Manager role (or an equivalent hybrid technical/product role) within a small team environment.
3 Strong technical and data fluency. Comfortable reading SQL, understanding how data pipelines and schemas work, and speaking engineer-to-engineer about data contracts, quality, and architecture.
3 Experience owning a product or feature area end to end, from data/requirements through to shipped, measurable outcomes.
3 A track record of using data and metrics (funnel, quality, usage) to drive prioritization decisions, not just track them.
3 Excellent written communication. Comfortable producing clear specs, dashboards, and updates for both technical and client-facing audiences.
3 Fluency with modern PM tooling (Linear, Notion, or equivalents) and with using AI tools (e.g., Claude or similar) as a regular part of your own workflow.
Helpful, not required
3 Experience with consumer panels, market research, or behavioral/passive data capture products.
3 Web scraping and social listening experience, as well as purchasing third party data when appropriate.
3 Familiarity with BigQuery, PostgreSQL, or similar warehouse/analytics tooling.
3 Experience working with or managing enterprise/blue-chip clients.
3 History building high performing mobile app products.
3 Experience shipping AI/NLP-powered features, not just using AI tools day to day.
