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- Tasks: Join a dynamic team to tackle real-world quantitative finance projects and make impactful decisions.
- Company: Morgan Stanley is a leading global financial services firm known for innovation and excellence.
- Benefits: Gain hands-on experience, mentorship, and networking opportunities in a collaborative environment.
- Why this job: Explore the fast-paced world of finance while developing your skills alongside industry leaders.
- Qualifications: Ideal candidates are pursuing or have completed a Masters/PhD in math, stats, or related fields.
- Other info: Coding assessment may be required; submit CV and cover letter in English only.
The Morgan Stanley Quantitative Finance Off-Cycle Internship Program in London runs for six months and is aimed at students who are required to complete a long-term internship as part of their studies or have already graduated. It is designed to help you explore opportunities within Quantitative Finance by working with desk strategists to evolve into an integral member of the team.
Quantitative Finance Interns are placed in a strategists (‘strats’) team related to their specialism, but will typically be partnered with particular business lines or desks to work on specific projects or models.
You can expect to take on significant responsibility as soon as you start. You will work directly with desks at a senior level, applying your skills and subject-matter expertise, to help them make strategic decisions, develop quantitative edge, 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 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 who design, implement, back-test, deploy and measure sophisticated automated trading components and systematic trading strategies. Working closely with other Strategists and trading desks, they rapidly provide new solutions and bring efficiencies and quantitative edge to existing business processes within a dynamic market-driven environment.
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
Curiosity, creativity, willingness to bring new ideas to the table, and approach problems differently
Background in mathematics, statistics, engineering, computer science, or related field in an academic setting
You have a keen interest in the financial markets and the drive and desire to work in a fast-paced, team-oriented environment
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
You have or are studying towards a Masters or PhD level degree and graduated in 2024 or graduating in 2025
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)
2025 Quantitative Finance Off Cycle Internship (London) employer: Morgan Stanley
Contact Detail:
Morgan Stanley Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land 2025 Quantitative Finance Off Cycle Internship (London)
✨Tip Number 1
Make sure to familiarize yourself with the latest trends in quantitative finance and trading strategies. This knowledge will not only help you during interviews but also demonstrate your genuine interest in the field.
✨Tip Number 2
Network with current or former interns and employees at Morgan Stanley. They can provide valuable insights into the internship experience and may even offer tips on how to stand out during the selection process.
✨Tip Number 3
Brush up on your coding skills, especially in languages commonly used in quantitative finance like Python or R. Being able to demonstrate your technical abilities can set you apart from other candidates.
✨Tip Number 4
Prepare for potential coding assessments by practicing relevant problems on platforms like LeetCode or HackerRank. This will help you feel more confident and ready to tackle any challenges that come your way.
We think you need these skills to ace 2025 Quantitative Finance Off Cycle Internship (London)
Some tips for your application 🫡
Tailor Your Cover Letter: Make sure to customize your cover letter for the Quantitative Finance Off-Cycle Internship. Highlight your relevant skills in mathematics, statistics, or computer science, and express your enthusiasm for working in a fast-paced, team-oriented environment.
Showcase Relevant Experience: In your CV, emphasize any previous internships, projects, or coursework that relate to quantitative finance, data analysis, or programming. Use specific examples to demonstrate your problem-solving skills and attention to detail.
Prepare for Coding Assessment: Since you may be required to complete a coding assessment, brush up on your programming skills. Familiarize yourself with common algorithms and data structures, and practice coding problems that are relevant to quantitative finance.
Proofread Your Application: Before submitting your application, carefully proofread both your CV and cover letter. Ensure there are no grammatical errors and that your documents are clear and concise. A polished application reflects your attention to detail.
How to prepare for a job interview at Morgan Stanley
✨Show Your Curiosity
Demonstrate your curiosity about the financial markets and quantitative finance during the interview. Prepare insightful questions that reflect your understanding of the industry and the specific role, showing that you are eager to learn and contribute.
✨Highlight Relevant Skills
Make sure to emphasize your background in mathematics, statistics, or computer science. Be ready to discuss specific projects or experiences where you applied these skills, especially in a team-oriented environment.
✨Prepare for Technical Questions
Since this role may involve a coding assessment, brush up on relevant programming languages and quantitative techniques. Be prepared to solve problems on the spot and explain your thought process clearly.
✨Communicate Effectively
Practice articulating your thoughts clearly and concisely in both written and verbal English. Good communication is key, especially when discussing complex quantitative concepts with senior team members.