Quant Analytics Senior Associate

4 days ago

Hyderabad, India JPMorgan Chase & Co. Full time

Join us to shape the future of customer engagement through data-driven insights and intelligent automation As a Customer Interaction Taxonomy Senior Associate in the AI/ML Solutions team within Data & Analytics, you will design, govern, and evolve the data taxonomy and semantic structures that unify Chase’s customer interaction events across channels. You will collaborate across technology, product, and analytics teams to ensure interaction data is consistently described, discoverable, and usable for analytics, personalization, and machine learning applications. Job responsibilities Design, maintain, and evolve enterprise-wide taxonomy for customer interaction data Implement consistent naming conventions and metadata standards for accurate event classification Partner with business and technology teams to incorporate new interaction events into the taxonomy Collaborate with engineering and analytics teams to deploy scalable semantic layers Contribute to data modeling efforts supporting reporting, AI, and ML use cases Support data and AI initiatives by enabling robust personalization and analytics Develop and document methodologies, governance processes, and playbooks for taxonomy standards Required qualifications, capabilities, and skills 3+ of experience in product, business analyst, or data analyst roles within large-scale data environments Expertise in taxonomy design, metadata management, or data modeling concepts Strong analytical and problem-solving skills to translate complex data concepts into actionable structures Proficiency in SQL or other querying languages for data validation and taxonomy mapping Advanced Microsoft Excel and data organization skills with large, complex datasets Experience working cross-functionally with product, analytics, and technology teams Background in enterprise data strategy, taxonomy automation, or ontology development Preferred qualifications, capabilities, and skills Experience building or managing semantic layers, knowledge graphs, or business glossaries Familiarity with data governance platforms or data warehouse solutions Understanding of AI/ML frameworks such as reinforcement learning, embeddings, or vector database search Bachelor’s or Master’s degree in Information Science, Data Analytics, Computer Science, or related discipline

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