We are looking for a Product Manager to join our Gen AI Intelligence team, owning the end-to-end data platform that powers our next-generation products.
Your core mandate:
Own a product area end-to-end within Gen AI Intelligence-from the underlying data and pipelines, through the user-facing experiences, to how customers extract value via APIs and integrations.
Define what data we need, how we structure it, and how we expose it to users and downstream systems
Deeply understand user workflows and jobs-to-be-done to identify the highest-leverage data solutions
Partner with Data Science to translate models and extractions into usable, reliable data pipelines
Ensure data quality, coverage, and governance across our Gen AI data estate
Drive product development end-to-end: from discovery through definition, prototyping, design, development, and deployment-with continuous iteration
Collaborate across a multi-disciplinary team: data scientists, data engineers, full-stack developers, UX designers, product marketers, and business stakeholders
What you'll do day-to-day
Obsess over user context: Understand how SEO practitioners, content marketers, and marketing leaders actually work-what questions they're trying to answer, what data would unlock value, and where current solutions fall short
Define data products end-to-end: From discovery through definition, schema design, pipeline development, and delivery-ensuring consistent quality and velocity
Connect data to user outcomes: Work closely with product teams that consume your data (reporting UX, recommendations, APIs) to ensure the data products actually solve user problems
Partner deeply with Data Science and Engineering: Translate DS models into production-ready data products; define requirements for data engineering pipelines; prioritize platform investments;
Define the core metrics, datasets, reports, and insights that will be made available to our users through our SaaS platform, APIs and MCPs.
Own data quality and coverage: Define metrics for data completeness, accuracy, and freshness; build feedback loops to continuously improve
Make tradeoffs with evidence: Use quantitative and qualitative analysis and user research to prioritize ruthlessly-not everything can be built, so you need to know what matters most
Your core mandate:
Own a product area end-to-end within Gen AI Intelligence-from the underlying data and pipelines, through the user-facing experiences, to how customers extract value via APIs and integrations.
Define what data we need, how we structure it, and how we expose it to users and downstream systems
Deeply understand user workflows and jobs-to-be-done to identify the highest-leverage data solutions
Partner with Data Science to translate models and extractions into usable, reliable data pipelines
Ensure data quality, coverage, and governance across our Gen AI data estate
Drive product development end-to-end: from discovery through definition, prototyping, design, development, and deployment-with continuous iteration
Collaborate across a multi-disciplinary team: data scientists, data engineers, full-stack developers, UX designers, product marketers, and business stakeholders
What you'll do day-to-day
Obsess over user context: Understand how SEO practitioners, content marketers, and marketing leaders actually work-what questions they're trying to answer, what data would unlock value, and where current solutions fall short
Define data products end-to-end: From discovery through definition, schema design, pipeline development, and delivery-ensuring consistent quality and velocity
Connect data to user outcomes: Work closely with product teams that consume your data (reporting UX, recommendations, APIs) to ensure the data products actually solve user problems
Partner deeply with Data Science and Engineering: Translate DS models into production-ready data products; define requirements for data engineering pipelines; prioritize platform investments;
Define the core metrics, datasets, reports, and insights that will be made available to our users through our SaaS platform, APIs and MCPs.
Own data quality and coverage: Define metrics for data completeness, accuracy, and freshness; build feedback loops to continuously improve
Make tradeoffs with evidence: Use quantitative and qualitative analysis and user research to prioritize ruthlessly-not everything can be built, so you need to know what matters most
Requirements:
Must-haves:
3+ years as a Product Manager on data-centric products (data platforms, analytics products, ML-powered features, or similar)-you've shipped data products that users depend on
Experience working in a data company or on data products where the core value proposition was derived from data (not just "we use data")
Strong analytical and data skills: You're comfortable querying data, analyzing patterns, and making data-informed decisions. You can hold your own in conversations about data modeling, schemas, and pipelines
Deep user empathy and research skills: You don't just build what stakeholders ask for-you dig into user workflows and jobs-to-be-done to find the real problem worth solving
Experience working with Data Science and Data Engineering teams: You know how to translate between DS/ML outputs and production systems, and you understand the tradeoffs involved
Strong communication skills: You can write a clear PRD, present to leadership, and align cross-functional teams around a shared vision
Strong pluses:
SQL proficiency: You can write queries to explore data, validate hypotheses, and QA outputs
Python or other scripting ability: You can prototype analyses, automate checks, or dig into data yourself when needed
Experience in digital marketing, SEO, or adjacent domains: Understanding of how marketers think about search, content, and visibility
Experience with B2B SaaS and enterprise customers: You understand long sales cycles, packaging, and the needs of mid-market/enterprise buyers
Mindset:
Curiosity over credentials: You want to understand how things work, not just ship features.
Must-haves:
3+ years as a Product Manager on data-centric products (data platforms, analytics products, ML-powered features, or similar)-you've shipped data products that users depend on
Experience working in a data company or on data products where the core value proposition was derived from data (not just "we use data")
Strong analytical and data skills: You're comfortable querying data, analyzing patterns, and making data-informed decisions. You can hold your own in conversations about data modeling, schemas, and pipelines
Deep user empathy and research skills: You don't just build what stakeholders ask for-you dig into user workflows and jobs-to-be-done to find the real problem worth solving
Experience working with Data Science and Data Engineering teams: You know how to translate between DS/ML outputs and production systems, and you understand the tradeoffs involved
Strong communication skills: You can write a clear PRD, present to leadership, and align cross-functional teams around a shared vision
Strong pluses:
SQL proficiency: You can write queries to explore data, validate hypotheses, and QA outputs
Python or other scripting ability: You can prototype analyses, automate checks, or dig into data yourself when needed
Experience in digital marketing, SEO, or adjacent domains: Understanding of how marketers think about search, content, and visibility
Experience with B2B SaaS and enterprise customers: You understand long sales cycles, packaging, and the needs of mid-market/enterprise buyers
Mindset:
Curiosity over credentials: You want to understand how things work, not just ship features.
This position is open to all candidates.
