2027 Data & AI Program - Summer Internship - Analyst - United States

JPMorgan Chase JPMorgan Chase · Banking · Chicago, IL +1 · Corporate Sector

Internship role focused on building and deploying AI/ML solutions, including generative AI and agent-based systems, within a regulated financial services environment. Responsibilities include data pipeline development, model building, insights generation, and ensuring data governance and compliance. Utilizes modern tools and platforms on AWS.

What you'd actually do

  1. Build intelligent systems that power real business outcomes, from machine learning models to generative artificial intelligence and agent-based solutions.
  2. Work hands-on with cutting-edge technologies to design, develop, and deploy artificial intelligence capabilities that automate processes and enhance decision-making.
  3. Apply data, statistics, and modeling to solve complex problems and generate actionable insights.
  4. Develop predictive models, test hypotheses, and analyze trends to help teams make smarter, data-driven decisions.
  5. Support data governance, risk management, and data standards to help ensure data is secure, trusted, and ready for artificial intelligence use.

Skills

Required

  • Pursuing a Bachelor’s or Master’s degree in a quantitative or technical discipline (e.g., Data Science, Machine Learning, Computer Science, or Mathematics).
  • Graduating between December 2027 and August 2028.
  • Authorized to work permanently in the United States.

Nice to have

  • Demonstrates strong knowledge of machine learning, data science principles, including prompt engineering, with experience handling large, complex datasets.
  • Use programming languages such as SQL and Python.
  • Use data & artificial intelligence tools (e.g., AWS, CoPilot, Snowflake, DataBricks, LLM).
  • Understand data management and governance, including data platforms, pipelines, models, taxonomies, metadata, lineage, privacy, and regulatory compliance.
  • Apply strong quantitative and analytical problem-solving skills to design experiments and deliver measurable outcomes (e.g., key performance indicators, uplift, return on investment).
  • Communicate clearly in writing and verbally to translate technical work for business stakeholders and collaborate across agile, cross-functional teams.
  • Translate business objectives into testable hypotheses and analytical plans, develops models and experiments, and communicates actionable recommendations to stakeholders.

What the JD emphasized

  • agent-based solutions
  • generative artificial intelligence
  • data governance
  • risk management
  • regulatory compliance

Other signals

  • build end-to-end data, analytics, and artificial intelligence and machine learning solutions
  • develop production-ready models
  • leverage modern tools (e.g., AWS, CoPilot, Snowflake, DataBricks, LLM)
  • build intelligent systems that power real business outcomes, from machine learning models to generative artificial intelligence and agent-based solutions
  • apply data, statistics, and modeling to solve complex problems
  • support data governance, risk management, and data standards to help ensure data is secure, trusted, and ready for artificial intelligence use
  • implement controls, improve data quality, and enable frameworks and structures that make solutions safe, scalable, and effective