Senior Product Manager, AI & Data Science Products

About the position The Senior Product Manager, AI & Data Science Products owns Crunchbase’s customer-facing AI data layer: proprietary data and intelligence generated from foundational data using AI and machine learning. The primary charter is to identify high-value opportunities for new model-derived data, validate their value with customers, and take successful products from experimentation through scaled adoption. Success is measured by three outcomes: New differentiated data, Higher customer value, and Revenue and adoption. Responsibilities • Own the strategy and roadmap for Crunchbase’s customer-facing AI data layer. • Identify high-value opportunities for new predictions, classifications, signals, and insights that improve customer decisions. • Build a differentiated portfolio of AI data products rather than isolated AI features. • Partner with Foundational Data to determine when customer needs are best addressed through collected, acquired, inferred, predicted, or generated data. • Work directly with customers to identify where new or better data can materially improve their workflows and decisions. • Rapidly test new AI data concepts, validate customer value, and scale successful products. • Define how model-derived data, including confidence and uncertainty, should be presented to customers. • Partner with Design, Engineering, and Data Science to deliver AI data across Crunchbase products, APIs, MCP, and data delivery experiences. • Define quality standards and evaluation frameworks for model-derived data in partnership with Data Science. • Determine when an AI data product is sufficiently reliable for scaled customer use. • Balance customer value, coverage, accuracy, freshness, and generation cost. • Monitor product and data performance and continuously improve quality based on customer feedback and observed outcomes. • Drive adoption of AI data products across Crunchbase’s customer experiences and distribution channels. • Partner with Go-to-Market on positioning, customer education, and launch strategy. • Partner with Pricing and Packaging and Sales to identify monetization opportunities. • Measure adoption, retention, expansion, revenue, and customer outcomes to determine which products to scale, improve, or retire. Requirements • Strong product judgment across customer discovery, strategy, prioritization, experimentation, and tradeoffs. • Strong understanding of data products and how customers derive value from proprietary data and insights. • Practical understanding of modern machine learning and AI capabilities and limitations. • Working knowledge of applied data science and machine learning. • Ability to translate product requirements for Data Science and Engineering teams. • Familiarity with model evaluation concepts such as precision, recall, confidence, and model drift. • Ability to reason about probabilistic and imperfect data and define appropriate quality thresholds. • Strong analytical skills and ability to balance customer value, quality, coverage, cost, and speed. • Excellent customer discovery, communication, and cross-functional leadership skills. • 3+ years of Product Management, Data Product Management, AI/ML Product Management, or comparable experience. • Experience owning customer-facing data science products from problem definition through launch and ongoing monitoring. • Experience partnering closely with Data Science and Engineering teams. • Demonstrated experience taking products from customer discovery and experimentation through scaled adoption. • Ability to define quality criteria that reflect customer needs and make informed quality and coverage tradeoffs. Nice-to-haves • Experience with B2B SaaS, data products, APIs, intelligence platforms, or commercializing differentiated data preferred.