Senior Taxonomist/Ontologist

Phyton Talent Advisors · New York

FULL TIME

Job Description

Seeking an experienced

Ontologist and Taxonomist with 5+ years of experience

applying the Web Ontology Language (OWL) to financial and economic analysis. The ideal candidate will have strong expertise in ontology development, taxonomy management, semantic technologies, and financial data, along with experience in natural language processing (NLP), named entity recognition (NER), and data science. The role involves maintaining financial ontologies and taxonomies, collaborating with business and technology teams, validating AI/LLM-generated results, and improving document tagging and search accuracy across financial research content.

Required Skills & Qualifications

1. Ontologies & Semantic Technologies

Strong, advanced-level expertise in

OWL (Web Ontology Language)

and

SPARQL .

Familiarity with

SKOS

and at least one additional industry ontology.

Familiarity with

GIST ontology

is a plus.

Experience developing and maintaining ontologies, taxonomies, concepts, entity definitions, and semantic relationships.

Excellent written and verbal communication skills, with the ability to create clear, accurate, and comprehensible definitions.

2. Financial & Economic Knowledge

Understanding of financial and economic analysis, including

Company filings, financial statements, and research reports.

Products, services, commodities, and industry analysis.

Macroeconomic factors and economic trends.

Familiarity with financial reference data, including

Stock tickers and market prices.

Corporate ownership structures and hierarchies.

Knowledge of financial instruments, including stocks, bonds, structured products, currencies, and derivatives.

3. Natural Language Processing (NLP) & AI

Experience with natural language processing techniques.

Knowledge of

Named Entity Recognition (NER)

and regular expressions.

Familiarity with large language models (LLMs) and model-output validation.

Ability to support automated testing and manual validation of AI/model-generated results.

4. Programming & Technical Skills

Familiarity with scripting languages such as

Python and/or shell scripting .

Some programming experience in at least one major language, such as

Java, C++, or C# .

Familiarity with data science and machine learning concepts.

Experience working with search technologies and document-tagging systems is beneficial.

Key Responsibilities

1. Ontology & Taxonomy Management

Maintain the Research Ontology and Trending Topics Taxonomy.

Define and incorporate new concepts and entities as they emerge in financial research and analysis.

Align ontology and taxonomy artifacts with internal Morgan Stanley reference data and data imported from external providers.

2. Business & Technology Collaboration

Consult with business stakeholders on projects involving NLP, ontologies, taxonomies, and related data.

Act as a bridge between business stakeholders and technology teams to translate business requirements into technical specifications.

Ensure requirements are accurately communicated, implemented, and validated in production systems.

Educate business and technology stakeholders on semantic technologies, ontologies, taxonomies, and relevant industry developments.

3. LLM & Model Validation

Support manual and automated validation of outputs generated by LLMs and other machine learning models.

Use automated testing tools, validation techniques, and subject-matter expertise to assess output quality and accuracy.

Help improve the reliability and consistency of model-generated results.

4. NLP, NER & Document Tagging

Collaborate with data science teams to integrate quantitative results into unstructured financial content.

Work with technologists supporting the

Mondeca platform

for named entity recognition and document tagging.

Ensure Mondeca applies NER rules correctly based on the established ontology and taxonomy.

Help troubleshoot and improve entity recognition and document-tagging accuracy.

5. Search & Information Retrieval

Collaborate with technologists supporting the

Elasticsearch index

containing hundreds of thousands of financial research reports.

Ensure the Mondeca platform correctly applies tags to documents and incorporates them into search functionality.

Improve search relevance and result accuracy through effective ontology-driven tagging and taxonomy integration.

Ideal Candidate Profile

The ideal candidate combines strong semantic technology expertise with financial domain knowledge and practical NLP experience. They can translate complex financial concepts into structured ontologies and taxonomies, collaborate effectively across business and technology teams, and help improve the accuracy of AI-driven tagging and financial research search systems.

Key Technical Keywords:

OWL, SPARQL, SKOS, GIST, Ontology Development, Taxonomy Management, Financial Services, Financial Instruments, Financial Reference Data, NLP, NER, Regular Expressions, Python, Shell Scripting, Java, C++, C#, LLM Validation, Machine Learning, Data Science, Mondeca, Elasticsearch, Semantic Technologies.

Company	Phyton Talent Advisors
Location	New York
Type	FULL TIME
Niche	Full-time