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Director, Ontology & Knowledge Architecture – Investment Data Standard

BNY
Posted 3 months ago, valid for 22 days
Location

New York, NY 10008, US

Salary

Competitive

Contract type

Full Time

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Sonic Summary

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  • The position of Director, Ontology & Knowledge Architecture – Investment Data Standard is available in New York, NY, for a candidate with over 10 years of experience in data modeling and ontology design.
  • The role involves leading the development of a unified Investment Data Standard (IDS) that supports data commercialization and interoperability across various platforms.
  • Key responsibilities include defining core entity models, establishing semantic crosswalks with external vendors, and designing ontology structures for analytics and AI capabilities.
  • Candidates should possess deep expertise in knowledge graphs and financial data domains, along with experience in enterprise-scale data models and metadata tools.
  • The salary for this position is competitive, reflecting the advanced skill set and leadership capabilities required.

Director, Ontology & Knowledge Architecture – Investment Data Standard

We’re seeking a future team member for the role of Director, Ontology & Knowledge Architecture – Investment Data Standard to join our Data & Analytics team. This role is located in New York, NY.

Role Overview:

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.

In this role, you’ll make an impact in the following ways: 

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)
     

To be successful in this role, we’re seeking the following: 

Domain & Technical Expertise

  • 10+ years in data modeling, ontology design, or knowledge architecture
  • Deep experience with
    • Knowledge graphs (RDF, OWL, property graphs)
    • Semantic modeling and taxonomy design
    • Entity resolution and identity management
  • Strong understanding of financial data domains:
    • Securities, pricing, corporate actions
    • Portfolio holdings, transactions, valuations
    • Private markets data structures

Architecture & Data Platforms

  • Experience designing enterprise-scale data models across multiple systems
  • Familiarity with
    • Snowflake / cloud data platforms
    • API-based data distribution
    • Metadata and catalog tools
  • Understanding of time-series data, event modeling, and data lineage

AI & Emerging Capabilities

  • 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

Leadership & Influence

  • 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

Preferred Qualifications

  • 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
     



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