JM
Programme
Internship
Location
London · Glasgow
About the role
This summer internship places analysts in JPMorganChase’s Data & AI function in London or Glasgow. Interns build end-to-end data, analytics, machine learning, and AI solutions, including models, pipelines, dashboards, and governance controls, while working in agile teams and receiving mentorship and training to deliver measurable business outcomes.
Role and Responsibilities
- Build machine learning, generative AI, and agent-based solutions supporting business outcomes.
- Design, develop, and deploy AI capabilities that automate processes and improve decision-making.
- Apply data, statistics, and modelling to solve complex problems and generate actionable insights.
- Develop predictive models, test hypotheses, and analyse trends for data-driven decisions.
- Support data governance, risk management, data standards, controls, and data quality improvements.
- Translate business objectives into analytical plans and communicate recommendations to stakeholders.
Programme Experience
- Work with global experts in agile, cross-functional teams across technology and business disciplines.
- Use tools including AWS, CoPilot, Snowflake, DataBricks, and large language models.
- Gain hands-on experience developing scalable data platforms, pipelines, models, and visualisation tools.
- Receive mentorship and training while building a foundation in data, analytics, and artificial intelligence.
- Potential locations are London and Glasgow.
Required Qualifications
- Pursue a bachelor’s or master’s degree in a quantitative or technical discipline.
- Relevant disciplines include data science, machine learning, computer science, or mathematics.
- Expected graduation must fall between December 2027 and June 2028.
- Applicants must be authorised to work in the U.S.; employment-based immigration sponsorship is unavailable.
Preferred Skills
- Knowledge of machine learning, data science principles, prompt engineering, and complex datasets.
- Programming experience with SQL and Python.
- Familiarity with data platforms, pipelines, models, taxonomies, metadata, lineage, privacy, and regulatory compliance.
- Strong quantitative, analytical problem-solving, written communication, and verbal communication skills.
- Ability to collaborate across agile, cross-functional teams and translate technical work for business stakeholders.