Senior Ontologist

Lenmar Consulting Inc; Alpharetta (GA); Hybrid; USD 188,000 - 267,000; Full time

Job summary

Lenmar Consulting Inc. invites a Senior Ontologist to lead Institutional Research ontology initiatives and taxonomic design for advanced financial analysis.

The hybrid role in Alpharetta, GA, partners with data science and business teams to maintain ontologies, support NLP/NER projects, and ensure accurate tagging and search across hundreds of finance reports. Expertise in OWL and SPARQL, SKOS, and financial data, plus Python or Java/C# development, will empower this position to shape technology

Qualifications

• Senior skills in OWL and SPARQL
• Familiarity with SKOS and industry ontologies
• Excellent language skills; craft precise definitions
• Understanding of financial analysis, filings, macroeconomics
• Familiarity with Wall Street reference data and instruments
• Experience with NLP/NER and regex
• Programming in Python and/or shell; Java/C++/C# experience
• Knowledge of data science and machine learning

Responsibilities

• Maintain the Research Ontology and Trending Topics Taxonomy with new concepts
• Consult with business on NLP projects involving ontology data
• Bridge between business stakeholders and technology implementers
• Aid validation of LLMs and other models using automated tools
• Educate stakeholders on semantic technologies, ontologies, and taxonomies
• Work with data science to integrate quantitative results into unstructured content
• Collaborate with vendor platform tech for NER and document tagging
• Work with Elasticsearch index to improve search result accuracy

Skills

OWL

SPARQL

SKOS

Python

Java

C++

NLP

NER

Tools

Elasticsearch

Job description

Senior Ontologist, Institutional Research consulting position with a leading financial company.

This role is hybrid in Alpharetta, GA

Rate up to $165/hour W2

An ontologist and taxonomist with 5+ years experience applying the Web Ontology Language (OWL) to problems in financial and economic analysis

Skills Required:

• ontology languages: senior skills in OWL and SPARQL required
• familiarity with SKOS and at least one other industry ontology; familiarity with gist a plus
• excellent language skills; skilled at crafting accurate and comprehensible definitions
• familiarity with the principles of financial and economic analysis, including company filings and reports; products, services, and commodities; industry analysis; macroeconomic factors; etc.
• familiarity with Wall Street-type reference data, including tickers, prices, corporate ownership hierarchies
• familiarity with the full variety of financial instruments: stocks, bonds, structured products, currencies, and their derivatives
• skilled at natural-language processing (NLP), including named entity recognition (NER), regular expressions, etc.
• programming languages: familiarity with scripting languages such as Python and/or shell; some experience in at least one major programming language such as Java, C++, or C#
• familiarity with data science and machine learning

Responsibilities and duties:

• Maintain the Research Ontology and Trending Topics Taxonomy, adding definitions of new concepts and entities as they arise in the world of financial analysis. Coordinate these artifacts with existing reference data within Morgan Stanley and imported from external providers.
• Consult with the business on projects involving natural-language processing and related ontology and taxonomy data.
• Work as a bridge between business stakeholders and technology implementers to ensure that requirements are accurately transmitted to implementers and accurately fulfilled in our systems.
• Aid in the manual and automatic validation of results from large-language models (LLMs) and other models, using automated testing tools and techniques and your own knowledge.
• Educate business and technology stakeholders on semantic technologies, ontologies, and taxonomies, including related developments in the industry.
• Work with the data science team to integrate quantitative results into unstructured content.
• Work with technologists supporting the vendor platform for named-entity recognition and document tagging. Ensure that that system's rules apply NER correctly based on the ontology and taxonomy.
• Work with technologists supporting the Elasticsearch index of hundreds of thousands of financial analysis reports. Work to ensure that the tag output of the system is properly applied to searches and documents in order to enhance search result accuracy.

Cindy Wing