Data Product Manager - AI/ML

About the Team:  As ServiceNow continues its unprecedented growth, the company seeks to further establish its advanced analytics AI/ML capabilities within the Finance & Strategy organization. The Finance & Strategy organization is undergoing a strategic transformation — and at the heart of this evolution is how we embed AI/ML to transform the way Finance works. The Finance Analytics & Insights (FA&I) team is the embedded analytics team within Strategic Finance for the Finance & Strategy organization as a whole. We are driving this shift through value and impact-based data products, strong cross-functional collaboration, and most importantly a product mindset.We are increasingly investing in AI to uncover insights and improve our financial forecasting and transformation through agentic AI for ServiceNow. This role will be the first hire to help drive a product transformation within the FA&I team.We are looking for an individual that is both detail oriented and able to think strategically while adapting to our fast-paced business. The ideal candidate is relentlessly curious, has high analytical capability, understands how to build a data product strategy and is passionate about driving business impact through AI technologies including agentic AI.We partner with our centralized Digital Technology (DT) and DT- Data & Analytics team to leverage the full data infrastructure, platform and advanced data & analytics capabilities, and we work directly with Product Finance as well as our Finance & Strategy teams to ensure we’re working hand in hand to define how finance & strategy organizations should set the bar in the 21st century.About the Role As a Data Product Manager – AI/ML, you will lead the development of AI and ML data products that transform how Finance operates. This is a people manager role with two global direct reports, and a strategic remit that cuts across finance & strategy. This role will work directly analytics & insights managers who support an individual finance business segment. The person in this role will help shape the Finance AI strategy and drive strategic conversations in how DT enables Finance meeting our AI powered vision.As a Data Product Manager, you’ll serve as a translator between business problems and AI solutions — understanding stakeholder needs, aligning business outcomes, working with development teams on prototypes, and ultimately delivering AI-powered products that scale and deliver value. This role is not about one-off models or dashboards. It’s about defining the future of AI in Finance and executing against that strategy.What you get to do in this role:Own the end-to-end AI/ML data product lifecycle — from discovery to delivery — aligned with Finance AI Strategy and business outcomes.Build deep empathy with users across Finance through persona development, Jobs-to-be-done, journey mapping, and outcome alignmentTranslate business needs into AI use cases; partner with dev teams to build POCs and bring ML models into productionTranslate OKRs into programs, projects, and agile work items (epics, stories, tasks)Drive agile ceremonies, roadmaps, and product artifacts including product requirements, mockups, and UI design reviewsEnsure the AI/ML solutions are usable, valuable, and adopted — with strong feedback loops, change management, and storytellingCollaborate cross-functionally with Product Finance (BPMs), Analytics Portfolio Managers, and Digital TechnologyCommunicate effectively across technical and non-technical audiences — from execs to developersFoster a product mindset across the team by mentoring and modeling best practicesManage stakeholders, communicate product priorities, and build alignment. Work with cross-functional teams to execute the product roadmap and deliver high-quality solutions. Take ownership and drive outcomes, regardless of role or organizational boundaries. Define the roadmap for our analytics products.Contribute to a high-performing team that delivers meaningful outcomes. Influence other product teams as a domain expert. Experience in leveraging or critically thinking about integrating AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI’s potential impact on the function or industry