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Salary
≈ $224k – $432k per year (Estimated)
Location
In office (New York)
Seniority
Senior · 3+ years exp
Visa
H-1B filings in 12 months: 3,429 · for this role: 2,086 · green card filings: 933

Confirmed on the employer's own hiring board on Nov 1, 2026. First seen by Alion on Aug 21, 2026. JPMorganChase scores A on the Alion truth index.

Overview
Company
Impact
Profile match
JPMorganChase is the largest bank in the United States by assets and one of the most systemically important financial institutions in the world, with a lineage running back through more than a thousand predecessor firms to the 1799 founding of the Bank of the Manhattan Company. It combines a dominant investment bank and markets business with Chase, the largest retail banking franchise in America, plus commercial banking and asset and wealth management. Headquartered in New York, the group is unusual among banks for the scale of its technology spending, running one of the largest engineering organisations of any financial institution and deploying its own internal AI platform across the firm.

Corporate & Investment Bank, Wholesale Payments Data and Analytics is responsible for executing big data analytics projects in response to product innovation for Merchant Services. Tangible output of the programs are insights that drive optimization of location and targeted marketing strategy for small business merchants, as well as deep consumer and business insights. You’ll engage in projects that integrate data science, research, and business domain expertise, focusing on analytics, business intelligence, data engineering, and visualization.

As AI Data Scientist Senior Associate within Payments Data and Analytics, you will involve leveraging your technical skills and business acumen to collaboratively design and implement end-to-end solutions with tangible commercial impact for our clients and customers, including chat assistants and workflow automations powered by LLMs and multi-agent patterns. You will develop data pipelines and dashboards, prototype and iterate on new generative AI capabilities and features, and ensure the quality, integrity, and reliability of our intelligent solutions through testing, evaluation, and monitoring. Your contributions will help streamline operations, enhance decision-making, and foster growth through innovative AI applications.

Job Responsibilities

  • Conceptualize solutions that automate and optimize business processes.
  • Design and refine prompts to improve AI model performance. Work with subject matter experts to align prompts with business goals and user needs.
  • Iterate designs to enhance functionality and user experience. Conduct rigorous testing for reliability and effectiveness.
  • Use tools like Snowflake, Python, and Tableau to create data pipelines and dashboards. Support AI-driven insights and decision-making.
  • Monitor AI model performance. Identify areas for enhancement. Implement updates to maintain quality and relevance.
  • Partner with data owners, department managers, data engineers and other stakeholders to aid in the development of data models and algorithms
  • Support Customer Insights applications, as well as custom client analytics requests on an ad hoc basis.

Required Qualifications, Capabilities, and Skills

  • Master’s Degree in Science, Technology, Engineering, Mathematics (STEM) or a related field.
  • Proficiency in Python and SQL for data processing and analysis.
  • 3+ years relevant work experience.
  • Expertise in quantitative research techniques and analytics using Python.
  • Proven critical thinking and creative problem-solving skills with ability to translate strategy into deliverables.
  • Knowledge of machine learning/data science theory, techniques, and tools.
  • Experience in leveraging Large Language Models (LLMs) and agent AI techniques.
  • Ability to collaborate effectively and cultivate strong partnerships.

Preferred Qualifications, Capabilities, and Skills

  • Experience in data analysis, data science, or a related field.
  • Familiarity with AWS, Snowflake for data management and analysis.
  • Attention to detail with a proven ability to learn new concepts and skills quickly.
  • Understanding of quality assurance practices and the importance of data integrity.
  • Ability to clearly develop and document analytic requirements with stakeholders.
  • Familiarity with evaluation/monitoring concepts for GenAI solutions (e.g., test cases, human-in-the-loop feedback, basic quality metrics) to support reliable deployments.
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