Director, Ontology & Knowledge Architecture – Investment Data Standard

BNY Mellon•New York, NY

8h•Onsite

About The Position

We are seeking a Director, Ontology & Knowledge Architecture to design and lead the development of our Investment Data Standard (IDS) – a unified, cross-platform ontology that underpins all commercial data products, analytics, and deterministic AI capabilities across the firm. This role is foundational to our data commercialization strategy. You will define the semantic layer that connects data across BNY platforms (custody, payments, collateral, markets, etc.) and external data providers – enabling interoperability, auditability, and scalable product innovation. You will operate at the intersection of data modeling, knowledge graphs, AI/LLMs, and financial domain expertise, translating complex, fragmented data ecosystems into a coherent, extensible semantic framework.

Requirements

10+ years in data modeling, ontology design, or knowledge architecture
Deep experience with Knowledge graphs (RDF, OWL, property graphs)
Deep experience with Semantic modeling and taxonomy design
Deep experience with Entity resolution and identity management
Strong understanding of financial data domains: Securities, pricing, corporate actions
Strong understanding of financial data domains: Portfolio holdings, transactions, valuations
Strong understanding of financial data domains: Private markets data structures
Experience designing enterprise-scale data models across multiple systems
Familiarity with Snowflake / cloud data platforms
Familiarity with API-based data distribution
Familiarity with Metadata and catalog tools
Understanding of time-series data, event modeling, and data lineage
Experience applying LLMs / AI to semantic alignment, data extraction, or ontology generation
Understanding of human-in-the-loop vs. automated model governance
Ability to design systems that balance probabilistic AI with deterministic data models
Proven ability to lead without authority across complex organizations
Experience driving enterprise standards adoption across multiple platforms
Strong communication skills – able to translate between technical teams and executive stakeholders

Nice To Haves

Experience in asset servicing, asset management, or financial data platforms
Background working with data vendors (Bloomberg, FactSet, MSCI, etc.)
Familiarity with industry standards (FIBO, XBRL, RIXML, ISO standards)
Experience building commercial data products or data marketplaces

Responsibilities

Define and Own the Investment Data Standard (IDS)
Architect and evolve a canonical ontology for financial instruments, entities, transactions, events, and relationships across public and private markets
Establish core entity models (e.g., asset, issuer, portfolio, transaction, valuation, exposure) and their relationships
Define standardized attributes, hierarchies, and identifiers (e.g., BNY Asset ID, cross-platform symbology)
Ensure the ontology supports time-series data, event-driven modeling, and lineage
Enable Cross-Platform Interoperability
Map and harmonize data models across platforms
Design and maintain semantic crosswalks between internal systems and external vendors (Bloomberg, ICE, MSCI, etc.)
Partner with platform teams to ensure IDS adoption as the single source of semantic truth
Define rules for source selection, hierarchy resolution, and data conflicts
Power Data Products, Analytics, and AI
Design ontology structures that support: Total portfolio analytics (public + private assets), Marketplace data aggregation (Asset Intelligence), Client-configurable data models (Data Studio)
Enable AI/LLM-driven semantic alignment, entity resolution, and attribute extraction
Ensure ontology supports explainability, auditability, and deterministic outputs for regulated use cases
Build and Govern the Knowledge Graph
Translate ontology into a production-grade knowledge graph architecture
Define entity resolution strategies and linking logic across datasets
Establish versioning, lineage, and change management processes
Implement governance for schema evolution, extension requests, and deprecation
Lead Cross-Functional Collaboration
Partner with Product leaders across data commercialization pods, Engineering teams building data pipelines and APIs, Data governance and sourcing teams, Client platform teams
Facilitate ontology design workshops with SMEs across domains
Translate business use cases into formal semantic models
Establish Ontology & Governance Operating Model
Stand up and lead a cross-platform ontology council
Define processes for: Use case intake and prioritization, Semantic discovery and modeling, Validation with real data, Publication and adoption standards
Ensure alignment with enterprise data governance and metadata platforms (e.g., Collibra)