Senior Product Manager, AI & Data Science Products

Crunchbase•Trenton, NS

90d•$160,000 - $190,000

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 role identifies high-value opportunities for new model-derived data, validates their value with customers, and takes successful products from experimentation through scaled adoption. Success is measured by creating differentiated intelligence that cannot practically be produced through collection alone, improving customer value, and driving measurable usage, retention, expansion, and monetization. The role owns the strategy and roadmap for customer-facing AI data products, identifying opportunities for predictions, classifications, signals, and insights that improve customer decisions. It works with Foundational Data to determine whether customer needs are best addressed through collected, acquired, inferred, predicted, or generated data, and builds a differentiated portfolio rather than isolated AI features. The Senior Product Manager works directly with customers to discover workflow and decision-making needs, rapidly tests AI data concepts, and scales successful products. In partnership with Design, Engineering, and Data Science, the role delivers AI data across Crunchbase products, APIs, MCP, and data delivery experiences, including appropriate presentation of confidence and uncertainty. The role defines quality standards and evaluation frameworks with Data Science, determines when AI data is reliable enough for scaled use, and balances customer value, coverage, accuracy, freshness, and generation cost. It monitors product and data performance and improves quality based on customer feedback and observed outcomes. It also drives adoption, partners with Go-to-Market on positioning, education, and launches, works with Pricing and Packaging and Sales on monetization, and measures adoption, retention, expansion, revenue, and customer outcomes to decide what to scale, improve, or retire. This is not an internal AI tooling or general AI feature role, ownership of foundational data collection, sourcing, or operations, or ML research or data generation for its own sake. AI data must solve meaningful customer problems and create measurable value.

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.

Responsibilities

Own the strategy and roadmap for Crunchbase’s customer-facing AI data layer.
Identify high-value opportunities for 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 whether 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 improve workflows and decisions.
Rapidly test AI data concepts, validate customer value, and scale successful products.
Define how model-derived data, including confidence and uncertainty, is 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 improve quality based on customer feedback and observed outcomes.
Drive adoption of AI data products across Crunchbase 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.