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About JPMorgan Chase
JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.
JPMorgan Chase currently has
1219 open roles
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The Data Analytics and AI VP joins the Portfolio and Execution Management function within the Business Enablement and Transformation team. This leadership role focuses on evolving infrastructure platforms' data and decision intelligence capabilities to improve portfolio management, investment governance, and strategic execution. You will design and implement AI-enabled decision-support solutions using machine learning, predictive analytics, and generative AI techniques to identify risks, trends, and anomalies. Daily responsibilities include developing data solutions for management reviews, building impactful dashboards, and defining reusable analytics patterns and metrics. Required skills include proficiency with SQL, APIs, cloud-based data platforms, and data modeling. You must demonstrate experience with LLM-based solutions, Copilot technologies, and retrieval-augmented generation. The role solves complex problems regarding portfolio health and investment prioritization through automated, auditable, and scalable reporting.
Develop data solutions to support business reviews and identify opportunities for enterprise improvement.
Design and implement AI-enabled decision-support solutions using machine learning and predictive analytics.
Build impactful dashboards for leadership using data visualization and transformation tools.
Partner with technology and risk stakeholders to ensure AI reporting meets data lineage and access controls.
Define reusable analytics patterns, metrics definitions, and reporting standards to ensure scalable insights.
Gather requirements from stakeholders for key business metrics, data sourcing, and visualization.
Manage multiple complex workstreams simultaneously across various domains.
What we're looking for
Bachelor’s Degree or higher in a quantitative discipline such as Computer Science, Engineering, Applied Statistics, or Mathematics.
8+ years of hands-on experience developing analytical solutions in a fast-paced environment (preferably financial services) or management consulting.
Strong experience with enterprise data ecosystems including SQL, APIs, cloud-based data platforms, data modeling, and data integration architectures.
Experience leveraging Generative AI, LLM-based solutions, Copilot technologies, retrieval-augmented generation (RAG), or similar enterprise AI capabilities.
Demonstrated ability to structure ambiguous problems and synthesize quantitative and qualitative inputs into clear recommendations for senior executives.
Proven interpersonal leadership, influencing, and stakeholder management skills across a matrix.
Ability to independently manage multiple complex workstreams and prioritize ruthlessly to deliver high-quality outcomes.
Familiarity with infrastructure and cloud technology such as datacenter compute, storage, database, network, mainframe, or middleware (preferred).
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