Global Financial Data Ontologist & Taxonomy Architect

Massive; Atlanta (GA); Hybrid; USD 150,000 - 230,000; Full time

Job summary

Massive is seeking a Principal Financial Data Ontologist to design and govern foundational taxonomies, symbology, and entity models for global financial markets. This hybrid role blends financial domain expertise with data modeling and classification science to create globally consistent systems across instruments and datasets.

You will own conceptual correctness, scientific rigor, and semantic clarity behind data models.

Qualifications

• Deep experience with reference data, symbology, taxonomy, or instrument modeling.
• Expertise in global identifiers (ISIN, SEDOL, CUSIP, FIGI, RIC, OCC, futures symbology).
• Strong understanding of cross-asset market structure.
• Demonstrated ability to design scientifically rigorous, explainable, and consistent classification systems.
• Comfort writing Python or SQL for prototyping, validation, and data exploration.
• Exceptional written clarity—able to produce precise, formal definitions, and explain complex taxonomy decisions.
• Experience building or contributing to security master models, reference data systems, or entity graphs is a plus.
• Familiarity with ontology frameworks or graph modeling (OWL, RDF, Neo4j, knowledge graphs) is a plus.
• Exposure to fundamentals taxonomy (GAAP/IFRS line items) from a metadata or modeling perspective is a plus.

Responsibilities

• Design and maintain a canonical, cross-exchange symbology for global securities, with deterministic rules for identifiers, listings, cross-listings, derivatives families, and lifecycle events.
• Create academically rigorous classification systems for industries, instrument types, corporate structures, and event categories—formally defined, versioned, citable, and empirically justified.
• Develop and evolve a unified entity and relationship model spanning issuers, securities, people, organizations, funds, indices, derivatives, and other market participants.
• Build robust cross-identifier mapping frameworks across major global identifier standards (ISIN, SEDOL, CUSIP, FIGI, RIC, OCC, futures symbology, and exchange-specific codes), including conflict resolution and lineage tracking.
• Define and govern internal naming standards, metadata conventions, and semantic rules that ensure consistency and clarity across all datasets and data products.
• Establish principled, formal rules for how data elements relate and correspond, enabling reliable interoperability between diverse datasets and preventing ambiguous or incorrect data assumptions.
• Prototype classification logic, normalization rules, and validation algorithms using Python or SQL to test correctness, reproducibility, and practical applicability.
• Evaluate, reconcile, and harmonize incoming datasets from heterogeneous sources using transparent, deterministic, academically defensible methodologies.
• Produce clear, authoritative documentation describing the definitions, rules, and conceptual models behind the identifiers, taxonomies, and ontologies you design.
• Partner with product and data teams to integrate your models into internal data systems and customer-facing data products.

Skills

Ontology design

Data modeling

Reference data

Python/SQL

Written clarity

Entity graphs

Knowledge graphs

Education

Classification science

Tools

OWL/RDF

Neo4j

Job description

Massive is seeking a Principal Financial Data Ontologist to design and govern foundational taxonomies, symbology, and entity models for global financial markets. This hybrid role blends financial domain expertise with data modeling and classification science to create globally consistent systems across instruments and datasets.

You will own conceptual correctness, scientific rigor, and semantic clarity behind data models.