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Salary
≈ $160k – $285k per year (Estimated)
Location
In office (London)
Seniority
Senior

Confirmed on the employer's own hiring board on Nov 4, 2026. First seen by Alion on Oct 1, 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.

Join us in redefining how artificial intelligence accelerates business impact. As an AI & Data Scientist, you have the opportunity to shape the future of workforce analytics and drive meaningful change. You’ll collaborate with talented colleagues, leverage cutting-edge tools, and contribute to a pioneering operating environment. We invest in your growth, offering hands-on experience and the chance to make a real difference. Your expertise will help us deliver faster, smarter solutions that empower our organization.

As an AI & Data Scientist in the HR Data & Analytics team, you will apply advanced analytics, machine learning, and artificial intelligence techniques to transform workforce data into actionable insights and solutions. You will partner with business leaders, product teams, and technologists to develop models, evaluate outcomes, and deliver AI-powered capabilities that support evidence-based workforce decisions. You will contribute to building an artificial-intelligence-native operating environment, focusing on model factories, evaluation frameworks, and agentic engineering tools. Your work will help accelerate the delivery of innovative AI solutions within a regulated environment.

Job Responsibilities:

  • Design, develop, test, and deploy AI and machine learning solutions that address workforce and business challenges
  • Conduct statistical analyses, experiments, and model evaluations to generate actionable insights and recommendations
  • Contribute to model factories and evaluation frameworks that improve model quality, scalability, and operational efficiency
  • Apply agentic, specification-driven, and evaluation-driven development approaches to accelerate solution delivery
  • Partner with business stakeholders to translate requirements into analytical solutions and measurable outcomes
  • Collaborate with technology teams to build scalable, reliable, and secure analytics and AI products
  • Identify opportunities to reduce costs, improve controls, enhance employee experiences, and expand organizational capabilities through data-driven solutions
  • Support adoption of reusable methodologies, tools, and vendor capabilities where appropriate
  • Communicate findings and recommendations clearly to technical and non-technical audiences
  • Ensure adherence to all applicable risk, control, and governance requirements

Required Qualifications, Capabilities, and Skills:

  • Bachelor’s degree in AI, Data Science, Computer Science, Statistics, Mathematics, Engineering, Economics, or a related quantitative discipline
  • Experience developing and deploying machine learning or AI solutions using modern tools and techniques
  • Working knowledge of large language models, agentic frameworks, or generative AI technologies
  • Experience with statistical analysis, experimentation, and model evaluation methodologies
  • Proficiency in Python, SQL, and data science tooling used in enterprise environments
  • Strong analytical, problem-solving, and communication skills
  • Ability to manage multiple priorities and deliver results in a collaborative environment

Preferred Qualifications, Capabilities, and Skills:

  • Advanced degree in a quantitative discipline
  • Experience building automated machine learning or model evaluation workflows
  • Experience with AI, machine learning, or analytics solutions in a regulated environment
  • Familiarity with cloud-based data and analytics platforms
  • Experience collaborating across business, product, and technology teams
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