•Own product vision, strategy, and roadmap for artificial intelligence products, aligning to business growth targets, user needs, and firm risk management objectives
•Lead the end-to-end product lifecycle from ideation and planning through execution, launch, adoption, and continuous enhancements to improve cost efficiency, innovation, reusability, and reliability
•Define and govern the solution design and delivery approach, evolving product methodologies and standards to consistently meet business outcomes and quality expectations
•Drive responsible artificial intelligence and generative artificial intelligence implementation, including ethical practices, fairness, explainability, and controls for data drift and concept drift detection
•Architect artificial intelligence-integrated, data-first workflows that enable human-plus-machine collaboration and integrate with upstream and downstream systems to maximize automation and connectivity
•Partner with cross-functional teams (data science, engineering, workflow technology partners, user experience and interface design) to translate strategy into executable solutions and build high-impact products
•Prioritize features and delivery execution by defining user stories, acceptance criteria, sequencing, and ensuring on-time, high-quality releases
•Establish product performance measures by setting key performance indicators, monitoring outcomes and user feedback, and prioritizing investments and enhancements based on measurable impact
•Manage cross-functional delivery across a portfolio by overseeing product owners and the overall book of work for artificial intelligence, workflow, and integration teams to ensure successful implementation
•Coach product teams on best practices in market research, prototyping, storyboarding, mind-mapping, adoption strategies, and delivery excellence to raise capability and execution rigor
•Champion innovation and generative artificial intelligence transformation across JPMorganChase by staying current on advancements, guiding stability versus variability choices, and fostering an open learning culture
Required qualifications, skills, and capabilities:
•Hold a bachelor’s degree in computer science, data science, engineering, or a related field
•Demonstrate product owner (or similar) experience delivering artificial intelligence and machine learning products end-to-end
•Bring 10+ years of hands-on experience in data science, machine learning, and predictive analytics
•Apply strong understanding of artificial intelligence, machine learning, and data analytics, including large-scale data and distributed processing
•Utilize familiarity with model operations practices, including monitoring, retraining, and continuous integration and continuous delivery pipelines
•Operate effectively in agile delivery environments and use product management tools such as Jira or Trello
•Communicate clearly with strong stakeholder management skills in fast-paced environments with multiple priorities
•Solve complex problems using analytical, conceptual, and investigative skills to evaluate options and scenarios
•Build solutions using Python, structured query language, Alteryx, and PySpark
•Demonstrate capability with natural language processing and prompt engineering
•Leverage broad tool and platform exposure, including Confluence, Microsoft Power Platform (including Copilot Studio), Camunda business process management tools, cloud architecture on Amazon Web Services and Microsoft Azure, automation platforms such as UiPath, Xceptor, and Instabase, customer engagement systems, and workflow platforms