J.P. Morgan
Job Summary
As a Semantic Data Scientist in Data Governance Product, you will be an integral part of our cutting-edge Semantic Data Science team. Our projects and capabilities upscale the traditional Data Scientist role through the application of Semantic technologies into every stage of the Machine Learning lifecycle. Our vision is to increase the scalability and value of Artificial Intelligence and Machine Learning use cases through Semantic data integration and curation strategies. We also leverage advanced Semantic-based Artificial Intelligence and Machine Learning techniques to develop state-of-the-art prediction, forecasting, and agentic systems. Join a collaborative, passionate team where you will gain hands-on experience utilizing Semantic Data Science techniques to drive business impact in the firms Data Governance and Marketing domains.
Job Responsibilities
Model domain knowledge related to our Marketing businesses.
Build ontology and mapping files to integrate multi-platform data ecosystems.
Curate Machine-Learning ready knowledge graphs by querying petabytes of financial data.
Embed knowledge graphs into domain-specific vector spaces.
Concatenate embeddings into wholistic feature spaces.
Train Graph Neural Network models using embedded feature spaces.
Evaluate Graph Neural Network models using recommender-based scoring metrics.
Package Semantic capabilities into agentic tooling.
Orchestrate Artificial Intelligence Agents using Semantic tooling.
Required qualifications, capabilities and skills Bachelors or Masters Degree in Computer Science or related discipline. 2 years of work experience leveraging Semantic Data Science or related techniques Programming Languages Python, Java Query Languages SPARQL, SQL Semantic Vocabularies RDF, R2RML, OWL, RDFS, XSD Machine Learning Feature Engineering, Hyperparameter Optimization, Model Evaluation Preferred qualifications, capabilities and skills Python Libraries RDFLib, mOWL, PyKEEN Query Optimization and Rewriting Virtual Tables/Views, OWL QL Graph Machine Learning Knowledge Graph Embeddings, Graph Neural Networks
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Required qualifications, capabilities and skills Bachelors or Masters Degree in Computer Science or related discipline. 2 years of work experience leveraging Semantic Data Science or related techniques Programming Languages Python, Java Query Languages SPARQL, SQL Semantic Vocabularies RDF, R2RML, OWL, RDFS, XSD Machine Learning Feature Engineering, Hyperparameter Optimization, Model Evaluation Preferred qualifications, capabilities and skills Python Libraries RDFLib, mOWL, PyKEEN Query Optimization and Rewriting Virtual Tables/Views, OWL QL Graph Machine Learning Knowledge Graph Embeddings, Graph Neural Networks
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