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We are looking for a Principal Financial Data Ontologist to design and govern the foundational taxonomy, symbology, and entity models that define how we represent global financial markets. This is a hybrid role spanning financial domain expertise, data modeling, classification science, and light technical prototyping.

We are looking for a Principal Financial Data Ontologist to design and govern the foundational taxonomy, symbology, and entity models that define how we represent global financial markets. This is a hybrid role spanning financial domain expertise, data modeling, classification science, and light technical prototyping. You will create academically defensible, globally consistent systems for identifying, naming, categorizing, and relating every instrument, entity, and dataset across asset classes.

This is not a data engineering role, and it's not a product manager role. You will own the conceptual correctness, scientific rigor, and semantic clarity behind the data models and taxonomies we ship.

If you love turning messy, conflicting real-world data into clean, principled, explainable systems, and you want to build the market's most coherent ontology, this role is for you.

• 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.

• Deep experience with reference data, symbology, taxonomy, or instrument modeling at a market data vendor, exchange, quant fund, or similar organization.
• Expertise in global identifiers (ISIN, SEDOL, CUSIP, FIGI, RIC, OCC, futures symbology) and how they're assigned, maintained, and resolved.
• Strong understanding of cross-asset market structure, including equity listings, derivatives contracts, corporate actions, index composition, and exchange rules.
• 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.
• Experience designing internal data naming conventions, semantic layers, or entitlement systems is a plus.
• Academic background related to classification science, information architecture, applied ontology, or library science applied to finance is a plus.

At Massive we are on a mission to help developers build the future of fintech. We are committed to democratizing access to the world's financial market data and enabling developers to build the future of fintech. Join us and be part of a team that is revolutionizing the way we interact with money and value.

Massive is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws. We strictly prohibit and do not tolerate harassment or discrimination against employees, applicants, or any other covered persons because of race, color, religion, creed, national origin or ancestry, ethnicity, sex, gender, gender identity, age, physical or mental disability, citizenship, sexual orientation, past, current or prospective service in the uniformed services. To request a reasonable accommodation, please email careers@massive.com .

• Benefits for full time offers from Massive include, but are not limited to, comprehensive medical plans, 401(k), and unlimited time off.

Before submitting your application, please take a minute to review our Applicant Privacy Notice , which describes the data we collect, why we collect it, and how we use it. By submitting your application, you consent to our Applicant Privacy Notice .

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