Director, Data & AI Products USWM

RBC•Minneapolis, MN

1d•$140,000 - $230,000•Onsite

About The Position

This is a rare leadership role at the intersection of AI product management, domain-driven data architecture, and wealth management transformation. You will define and own the Data & AI product portfolio that powers Financial Advisor productivity, client intelligence, and revenue growth. You will operate as a true Product Owner owning vision, roadmap and outcomes across: • Data Products (domain-aligned, reusable, governed assets) • AI Products (agentic workflows, predictive insights, copilots) • Data Models (conceptual → logical → product-aligned implementations) This role sits at the center of a modern Data & AI operating model—bridging Digital Experience, Business, and Technology—with a mandate to build, test, and scale high-impact capabilities quickly while aligning to enterprise architecture and governance standards. Success in this role means products are not just delivered—but adopted, trusted and measurably drive business outcomes (e.g., FA productivity, client growth, risk reduction).

Requirements

Proven AI Product Ownership experience (ideally from organizations like Meta, Amazon, Block Inc., or Morgan Stanley)
Demonstrated ability to own and ship AI/ML-powered products end-to-end
Strong experience in product management disciplines: Roadmapping, backlog ownership, prioritization
Defining KPIs and driving measurable outcomes
Deep understanding of data product concepts: Domain-driven design
Data modeling (conceptual/logical alignment to products)
Data quality, lineage, and governance
Experience building AI-driven workflows or agentic systems
Ability to operate as both: Strategic leader
Hands-on individual contributor
Strong stakeholder management across business, engineering, and architecture

Nice To Haves

Wealth Management or Financial Services experience (advisor workflows, client lifecycle, portfolio insights)
Experience with CRM platforms (e.g., Salesforce) and AI integrations
Exposure to knowledge graphs, GraphRAG, or explainable AI frameworks
Familiarity with modern data platforms (e.g., Snowflake, real-time + analytical integration)
Background in multi-agent orchestration or AI platforms
Experience working in matrixed, regulated environments

Responsibilities

Own the Data & AI Product Lifecycle (End-to-End)
Define and execute product vision, strategy, and roadmap across Data and AI domains
Translate wealth management business needs into scalable, reusable product capabilities
Drive product lifecycle management: ideation → incubation → build → adoption → optimization
Ensure alignment to domain-driven data models (Client, Account, Positions, Transactions, etc.)
Act as a True AI Product Owner (Hands-On)
Write and prioritize product backlogs across AI, data, and modeling layers
Define clear product requirements (user stories, acceptance criteria, KPIs)
Partner closely with AI Engineering, Data Engineering, and Architecture to deliver solutions
Make trade-off decisions between vendor capabilities (e.g., agent platforms) and internal builds
Lead Data Product & Modeling Strategy
Ensure all products are built on trusted, governed, and reusable data assets
Drive standardization of data definitions, lineage, and quality across domains
Partner with Data Modeling and Governance teams to enforce consistency and scalability
Elevate data from “assets” to operable products (APIs, analytics layers, AI-ready datasets)
Deliver AI Products that Drive Advisor Productivity
Own AI use cases such as: Advisor copilots & agentic workflows, Client intelligence & next-best-action, Automated insights from transactional and behavioral data
Ensure AI products are: Explainable, Trusted, Embedded into advisor workflows (e.g., CRM, Salesforce)
Drive Adoption & Value Realization
Define and track product success metrics (usage, productivity lift, revenue impact)
Ensure products are actively used—not just delivered
Partner with field leadership and advisors to embed products into day-to-day workflows
Continuously iterate based on feedback and measured outcomes
Lead and Develop a High-Performance Team
Manage a team of ~6 (product managers, analysts, or hybrid roles)
Operate as a player–coach: mentoring while directly owning critical product areas
Establish strong product management discipline and culture (ownership, accountability, speed)