Staff Product Manager, Data & Platform

Kard is building commerce media infrastructure that connects financial institutions, financial-services platforms, and merchants through data and merchant-funded rewards. As our reach expands, we are building for a step-change in scale, and for opportunities ranging from more relevant rewards and marketer intelligence to new commerce and distribution models. About the Role As Staff Product Manager, Data & Platform, you will be the product lead for two established teams: Data, spanning ML, data science, analytics, and data engineering; and Engineering Enablement, which owns Kard’s internal developer platform and the infrastructure that moves data and supports reliable, real-time decisioning at scale. Together, these teams provide the intelligence and delivery foundations for Kard’s customer products. This is one of Kard’s most senior individual-contributor roles. Working with business and customer-facing product leaders, you will discover, shape, validate, and measure bets, turn foundational technology into customer and commercial value, and coach others to raise the quality of product thinking. Responsibilities Set and communicate a coherent strategy for Kard’s data and platform capabilities, turning company direction into focused bets that balance new products with platform leverage. Lead collaborative shaping with engineering, data, and business partners through Kard’s Shape Up process; clarify outcomes, appetite, risks, evidence, and measures of success. Turn transaction data, ML, and platform capabilities into products and business opportunities, including consumer, merchant, and location intelligence; targeting; marketer insights; and new applications of transaction intelligence. Advance the intelligence behind Kard’s offer platform, including personalization, merchant and location understanding, contextual decisioning, experimentation, and lift measurement across batch and real-time systems. Define reusable capabilities for offer decisioning, delivery, matching, measurement, and partner integrations; partner with customer-facing PMs on product definitions and end-to-end outcomes. Treat Kard’s data and developer platforms as products: understand technical users, expand self-service, reduce friction, and measure business impact, quality, trust, reliability, and speed. Desired Skills Experience leading technically complex data, ML, or platform products across multiple teams. A record of turning data or foundational technology into measurable customer and commercial value. Working fluency across several relevant domains—including data platforms, quality and governance, ML lifecycles, batch and real-time serving, APIs, cloud infrastructure, and developer platforms—and the ability to go deep without replacing engineering leadership. Fluency in experimentation and measurement, including A/B testing, lift or incrementality, and partnership with data scientists. Strong discovery and shaping skills with technical users and business stakeholders, and the ability to validate needs directly with external customers. Understanding of marketplace economics and marketer outcomes, and how targeting, relevance, measurement, and incentives create value; direct adtech experience is not required. The influence and judgment to align executives, leaders, and ICs; challenge assumptions constructively; make tradeoffs explicit; and commit to shared direction. Entrepreneurial judgment paired with durable thinking about scale, security, privacy, and compliance. Commitment to fostering an inclusive work environment and actively contributing to team growth and cohesion. U.S. core business hours availability and willingness to travel for company meetings. Bonus Points Experience in commerce media, card-linked offers, loyalty, fintech, adtech, or another transaction-intensive marketplace. Experience building marketer-facing insights, audience, measurement, or analytics products from first-party data. Experience with ML personalization, recommendations, merchant or location intelligence, entity resolution, or real-time decisioning. Experience with modern data or platform technologies such as Databricks, dbt, AWS, Kubernetes, and Terraform, especially at enterprise or regulated scale. Remote