In this role you will be the product owner for Advisor360°'s data fabric, the trust infrastructure that connects household relationships, account structures, and advisor context across the platform. Your job is to deepen that foundation: strengthening governance, quality, and product discipline as AI capabilities scale.
- Own the product strategy and roadmap for the data fabric's evolution, including data product contracts, lineage, metadata management, and quality observability
- Define what a "certified data product" means at Advisor360° and build the lifecycle to support it from registration through retirement
- Extend the fabric's governance model so domain teams can own their source-of-truth systems while the Data Fabric team provides shared standards, tooling, and quality frameworks
- Shape canonical data models, enriched entities, and AI-ready representations that ML and GenAI systems consume, building on the existing household and relationship models
- Champion developer experience across the data platform: APIs, MCPs, documentation, onboarding, and self-service access
- Partner with Compliance and Legal to ensure data governance meets the auditability, explainability, and regulatory standards required in wealth management
- Own vendor relationships and integration strategy for metadata management and data observability tooling
Data Science Operations
Product teams across Advisor360° build AI-powered features, and those features depend on Data Science and ML models. The engineers who build and maintain those models sit on your team. You manage that supply side.
- Manage prioritization and capacity for DS/ML engineering work across product teams, ensuring the team builds, retrains, and maintains the right models at the right time
- Own the operational health of DS/ML models in production, monitoring for drift, data quality degradation, and performance changes that product PMs may not have visibility into
- Partner with product PMs to translate their feature requirements into DS/ML engineering work; they define what "good" means for their users, and you ensure the models underneath reliably deliver on their intended outcomes
- Drive adoption of shared observability, validation, and monitoring tooling that gives product teams and leadership visibility into model behavior
- Provide clear reporting on DS/ML capacity, operational risk, and model health for Product, Engineering, and Executive leadership
Product PMs own quality and release decisions for their features. Your job is to make sure the DS/ML dependencies they rely on stay well-built, well-monitored, and never quietly degrade beneath them.
Cross-Functional Leadership
- Act as the single product interface for the Data Fabric team, coordinating across Data Science, AI Engineering, Platform Engineering, and domain product teams
- Drive alignment on prioritization and sequencing across teams that have historically operated independently
- Guide and mentor other Product Managers on data-informed practices, evaluation thinking, and working with technical platform teams
Who You Are
Core Requirements
- 7+ years of product management experience, with meaningful time on data platforms, data governance, developer tooling, or infrastructure products, ideally including experience scaling an existing platform through a major capability evolution
- Experience driving adoption of platform capabilities across teams that did not ask for them. You know that the hardest part of a data platform is not building it; it is getting people to use it
- Strong enough technically to hold your own in architectural discussions about data modeling, lineage, pipeline design, and system dependencies. You’re a builder that knows when something is wrong