2027 Quantitative Finance Off-Cycle Internship (London)

About the role

Six- to nine-month Quantitative Finance internship in London for students completing a long-term placement or recent graduates. Interns join front-office strategist teams aligned with sales or trading, developing quantitative models, trading tools, technologies, and data solutions while working closely with desks, technologists, risk managers, and senior stakeholders.

Responsibilities

• Develop and optimise trading strategies, models, tools, components, and workflows for sales and trading desks.
• Apply quantitative research, statistical techniques, machine learning, probability, and numerical analysis to trading problems.
• Support algorithmic trading, pricing, hedging, portfolio construction, data analysis, and trading risk management.
• Work with technology and trading teams to improve data infrastructure, quality, control, and commercialisation.
• Contribute to strategic decisions, quantitative capabilities, new technologies, operational efficiencies, and business changes.
• Build relationships with sales, trading, management, technologists, risk managers, and other firm functions.

Potential Role Areas

• Electronic Trading Strategists advise clients, optimise execution costs, and help evolve algorithmic trading solutions.
• Desk Strategists develop systematic trading strategies, models, tools, and workflows using statistics and machine learning.
• Modelling Strategists create pricing models and hedging strategies using applied probability and numerical analysis.
• Data Strategists use big data, machine learning, and artificial intelligence to improve data usage and infrastructure.

Training and Development

• Receive on-the-job training and individual sessions covering data resources, models, analytical tools, and artificial intelligence capabilities.
• Complete curriculum covering financial markets, product knowledge, and technical training.
• Gain continuing exposure to sales, trading, and management through networking with peers and colleagues.
• Receive mentorship, career guidance, corporate transition support, and connections across the Morgan Stanley network.

Requirements

• Have or be studying toward a Master's or PhD-level degree, graduating in 2026 or 2027.
• Have an academic background in mathematics, statistics, engineering, computer science, or a related field.
• Know Python, Scala, Java, KDB/q, C++, or a similar programming language.
• Demonstrate financial markets interest and motivation to work in a fast-paced, collaborative, team-oriented environment.
• Bring curiosity, creativity, practical problem-solving skills, attention to detail, and a willingness to propose new ideas.
• Communicate effectively in written and verbal English, with a pragmatic focus on timely delivery.

Application

• Submit a CV and covering letter in English.
• A coding assessment may be required; applicants will be notified if applicable.