In the Quantitative Finance division, we provide critical quantitative strategies and solutions for businesses across the Firm to optimize trading tools and processes.

Since 1935, Morgan Stanley is known as a global leader in financial services, continuously evolving and innovating to better serve our clients and our communities in more than 40 countries around the world.

‍

‍

PLACEMENT/DURATION

The Morgan Stanley Quantitative Finance Off-Cycle Internship Programme in London runs for 6 or 9 months with the possibility to rotate across teams. Aimed at students who are required to complete a long-term internship as part of their studies or have already graduated. The programme is designed to help you explore opportunities within finance by working with quantitative specialists to evolve into an integral member of the team. Quantitative Finance interns are placed in one or more front office strategists (‘Strats’) teams that are typically aligned to a sales or trading business to work on projects or models. You can expect to take on significant responsibility as soon as you start. You will work directly with sales and trading desks at a senior level and build partnerships with, and learn from, other firm functions such as technologist and risk managers. You will be expected to apply your skills and subject-matter expertise to help them make strategic decisions, develop quantitative edge and new technologies, drive efficiencies and effect changes.

‍

‍

‍

‍

TRAINING PROGRAM

‍
Training includes on-the-job training and one-on-one sessions to familiarize yourself with the Firm's data resources, models, analytical tools, and AIML capability. The curriculum covers market and product knowledge as well as technical training. Throughout the program, you will be continually exposed to Sales, Trading and Management, and you will benefit from networking opportunities with peers and colleagues. You will also be assigned a mentor to ease your transition into the corporate environment by offering career guidance, serving as a sounding board, and helping connect you to the broader Morgan Stanley network. Your co-workers are a diverse group who are motivated experienced industry leaders as well as graduates from top Universities that enjoy solving interesting problems in a collaborative environment.

‍

‍

‍

‍

RESPONSIBILITIES

‍
Strategists typically work very closely with desks across business lines, are commercially driven and revenue focussed.

‍

The below four profiles describe the different categories of roles available within Strats. In many cases an individual role will encompass aspects of each.

• Electronic Trading Strategists are financial and software engineers focus on clients who use our Algorithmic Trading suite. The goal is to advise, optimize and reduce the cost of execution.   You will become familiar with the design and implementation of our algorithmic suite and help shape it’s evolution.   The Strategists are client facing, so adaptability, personality and collaborative interpersonal skills are important
• Desk Strategists use statistical techniques and machine learning to develop and optimise trading strategies, tools, components and flows. Working closely with Electronic Trading Strategists and trading desks, they apply rigorous quantitative research and portfolio construction techniques to design systematic trading strategies and models.
• Modelling Strategists use applied probability and numerical analysis to create pricing models and hedging strategies that drive trading decisions. Working closely with trading desks, they enhance Morgan Stanley's ability to trade innovative products and improve the management of the Firm’s trading risk.
• Data Strategists use advanced big data, machine learning and AI techniques to facilitate data usage, analysis and commercialisation. Closely work with trading desk and technology to develop cutting edge innovative ways to improve data infrastructure, quality and control.

‍

‍

‍

‍

QUALIFICATIONS/SKILLS/REQS

• You have or are studying towards a Master or PhD level degree and have graduated in 2025 or graduating in 2026
• You have a background in mathematics, statistics, engineering, computer science, or related field in an academic setting
• You have knowledge of Python, Scala, Java, KDB/q, C++, or similar programming language
• You have a keen interest in the financial markets and the drive and desire to work in a fast-paced, team-oriented environment
• Curiosity, creativity, willingness to bring new ideas to the table, and approach problems differently
• Pragmatic approach to ensuring delivery on a timely basis
• You will possess practical problem-solving skills with a great attention to detail
• You are able to communicate effectively in both written and verbal English

‍

‍

‍

NOTE

• Please only submit a CV and Covering Letter in English only as part of your application
• You may be required to do a coding assessment as part of your application (you will be notified if this is required)

‍