Sr Ontologist and Taxonomist

Finance

Pay Rate is Open - US Citizen and GC - W2 Candidates only

Hybrid - 3 days in office, 2 remote per week

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 preferred, but ontology language experience 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 (msRo) 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 *** 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 Mondeca 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 Mondeca system is properly applied to searches and documents in order to enhance search result accuracy.

 

All your information will be kept confidential according to EEO guidelines.