Staff Product Manager, Data

Built is an AI-powered platform for construction and real estate finance. The Staff Product Manager, Data owns data capabilities and reporting tools, including analytics, portfolio insights, customer data integrations, and the data foundation for AI features. The role leads a team of data scientists and technical analysts and partners with engineering and product teams to deliver customer-facing data products.

Responsibilities:

• Own the strategy and roadmap for Built’s data capabilities, including embedded reporting and analytics, portfolio dashboards, data exports, and data sharing integrations
• Get close to how lenders, owners, and GCs use data to make decisions, and turn that into sharp problem statements and requirements
• Partner with data engineering on data models, pipelines, and data quality so the numbers customers see are accurate and on time
• Drive shared metric definitions so a figure like “percent complete” or “funds disbursed” means the same thing in every product and every customer workspace
• Work with the CLA, CLA+ and payments product teams so data is captured well at the source instead of cleaned up downstream
• Shape the data that powers Built’s AI features, including the AI Draw Agent and lender portfolio risk tools
• Track adoption and impact of your products and use what you learn to decide what to build next
• Support sales and customer success with demos, customer conversations, and enablement on platform reporting and data features
• Manage and develop a team of data scientists and technical analysts, setting clear priorities and balancing ongoing reporting needs with new feature development
• Guide data science initiatives from customer problem definition through validation and delivery, partnering with data scientists and engineers to turn models and insights into reliable features within Built’s products

Requirements:

• 5–8 years of product management experience, with at least 2 years owning data, analytics or reporting products in B2B SaaS
• Strong SQL and comfort working directly in the data
• Working knowledge of modern data stack concepts: warehouses, ELT, dimensional modeling, and BI or embedded analytics tools such as Sigma, Looker or Tableau
• Experience writing requirements for data work that a data engineer can build against, including metric definitions, data contracts and acceptance criteria
• A track record of shipping data features and analytics capabilities that customers adopt
• Ability to explain data concepts clearly to bankers and engineers alike
• Experience partnering directly with data scientists to deliver customer-facing capabilities, with enough fluency in statistical analysis, modeling, and validation to evaluate tradeoffs and explain results and limitations clearly
• Experience leading work with analysts on reporting and analytics products
• readiness to coach and develop data scientists and technical analysts is essential
• Prior people management experience is a plus
• Experience in financial services, lending, real estate, or construction is a strong plus