AI and Data Product Manager

Intercontinental Exchange, Inc. (ICE) is seeking an AI and Data Product Manager to lead the transformation of established business workflows by rebuilding them around AI-not by layering AI on top of them. This role owns the strategy, roadmap, and delivery of our AI-powered applications and data products, sitting at the intersection of business operations, data science, machine learning engineering, and our customers.

You will be part of a highly visible team central to ICE’s strategy to analyze mortgage and market data and deliver AI-driven insights to our clients in a meaningful, responsible, and scalable way.

Intercontinental Exchange, Inc. (ICE) is seeking an AI and Data Product Manager to lead the transformation of established business workflows by rebuilding them around AI-not by layering AI on top of them. This role owns the strategy, roadmap, and delivery of our AI-powered applications and data products, sitting at the intersection of business operations, data science, machine learning engineering, and our customers.

You will be part of a highly visible team central to ICE’s strategy to analyze mortgage and market data and deliver AI-driven insights to our clients in a meaningful, responsible, and scalable way. This is a process-transformation role first and a feature-delivery role second. We hire for the ability to decompose workflows and apply AI where it is verifiable-not for prior expertise in any specific industry.

A track record of entering an unfamiliar domain, mapping its workflows, and shipping something measurable is the signal we value most.

• Map and decompose existing business workflows end-to-end- identifying steps that are high-volume, high-variance, and verifiable- before deciding where AI belongs.
• Reimagine processes around AI rather than bolting AI onto current steps, prioritizing opportunities by the principle of volume, variance, and verifiability.
• Define and own the product vision, strategy, and multi-quarter roadmap for a portfolio of AI applications and data products aligned to business objectives.
• Size AI opportunities with conservative, evidence-based ROI assumptions, targeting tasks whose outputs can be reliably graded and avoiding "too much, too fast" over-commitment.
• Partner closely with data science and ML engineering to translate models—including predictive analytics, NLP, and LLM/generative AI and agentic solutions-into reliable, production-grade products.
• Design evaluation criteria and acceptance thresholds ("define good before building"); establish evals, blind review panels, and LLM-as-judge methods, and monitor for hallucination, bias drift, and model degradation in production.
• Architect human-in-the-loop workflows with expert review designed in, expanding automation only after each phase is proven.
• Productize ICE's proprietary data assets into well-defined data products such as APIs, data feeds, datasets, dashboards, and embedded analytics.
• Write clear product requirement documents (PRDs), user stories, and acceptance criteria; maintain and prioritize the product backlog within an Agile/Scrum environment.
• Define success metrics and KPIs (adoption, task success rate, model performance, revenue, ROI) and use data to measure outcomes and continuously improve products.
• Drive change management and adoption-bridging data scientists and business owners and getting non-technical stakeholders to embrace AI-changed workflows.
• Champion responsible AI in partnership with data science, risk, and compliance: model governance, bias and fairness, explainability, model risk, and data quality.
• Ensure products meet regulatory and data-governance requirements relevant to mortgage and financial services (e.g., MISMO, FNMA, FHLMC, GNMA, and…