Senior Product Manager, AI & Data Science Products

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🔥 0 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

📊 Data Scientist

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Crunchbase

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2007

☁️ SaaS

🤝 B2B

💰 $50M Series D on 2022-08

SaaS • B2B

Crunchbase is a subscription software platform that aggregates and delivers structured data, news, and predictive intelligence about private and public companies, funding rounds, acquisitions, leadership moves, and market activity. It provides paid products (Crunchbase Pro, Crunchbase Business), a marketplace, data licensing, and tools for investors, sales teams, and researchers to discover, track, and act on company intelligence.

📋 Description

• Own the strategy and roadmap for Crunchbase’s customer-facing AI data layer • Identify opportunities for predictions, classifications, signals, and insights that improve customer decisions • Build a differentiated portfolio of AI data products • Partner with Foundational Data to determine appropriate data approaches • Conduct customer discovery and validate AI data concepts • Define presentation of model-derived data, including confidence and uncertainty • Partner with Design, Engineering, and Data Science to deliver AI data across products, APIs, MCP, and data delivery experiences • Define quality standards and evaluation frameworks for model-derived data • Balance customer value, coverage, accuracy, freshness, and generation cost • Monitor and improve product and data performance • Drive adoption across customer experiences and distribution channels • Partner with Go-to-Market, Pricing and Packaging, and Sales on positioning, launches, and monetization • Measure adoption, retention, expansion, revenue, and customer outcomes to determine which products to scale, improve, or retire

🎯 Requirements

• 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 reflecting customer needs and make quality and coverage tradeoffs • Strong product judgment across discovery, strategy, prioritization, experimentation, and tradeoffs • Strong understanding of data products and customer 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 precision, recall, confidence, and model drift • Ability to reason about probabilistic and imperfect data and define quality thresholds • Strong analytical skills • Excellent customer discovery, communication, and cross-functional leadership skills • Experience with B2B SaaS, data products, APIs, intelligence platforms, or commercializing differentiated data preferred