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- Tasks: Join the QM team to develop and enhance quantitative models for financial securities.
- Company: ExodusPoint Capital, a leading multi-strategy investment firm in London.
- Benefits: Gain hands-on experience in a dynamic environment with potential for career growth.
- Other info: Internship duration is 3-6 months, perfect for building your skills.
- Why this job: Dive into the world of finance and data science while making a real impact.
- Qualifications: Pursuing a PhD or Master's in STEM with programming exposure.
The predicted salary is between 20000 - 30000 £ per year.
ABOUT EXODUSPOINT
ExodusPoint Capital, founded in 2017 by Michael Gelband, began managing investor capital in 2018. It is led by Michael Gelband (CEO, CIO and Co-Founder). The Firm employs a global multi-strategy investment approach, seeking to deliver compelling asymmetric returns by combining complementary liquid strategies managed by experienced investment professionals within a robust risk framework. ExodusPoint has brought together an accomplished team, with hands-on experience running multi-manager businesses, to create an institutional investment management firm.
ExodusPoint is seeking an entry-level candidate for an internship in the Quantitative Modeling (QM) team in London. The QM team is responsible for all aspects underlying the use of valuation and risk models for financial securities across asset classes. Moreover, many quantitative modeling applications rely ever increasingly on the use of historical and scenario data. The ideal candidate will thus have a well-rounded educational background in a STEM discipline, financial engineering, and data science (Machine Learning, Artificial Intelligence).
Responsibilities:
- Depending on educational background work on one or more of the following themes:
- Library Quantitative Development (e.g. pricing, financial or data model implementation related)
- Financial or Data Modeling Analytics (e.g. model improvements, securities pricing, financial or macro time series related)
- Front-End Application Development (e.g. end user applications in Excel or Python)
- Quantitative Analytics Infrastructure (e.g. quant analytics platform related)
Expected Duration: 3-6 months
Qualifications:
- Ongoing PhD level or Masters level studies from a top university in a STEM discipline
- Applied mathematics, statistics and computation focused STEM disciplines preferred
- Must have exposure to programming and development
- Exposure to applied mathematics, statistics, data science
- Exposure to financial engineering preferred, but not a must have
- Exposure to data science, ML and AI techniques is a plus
- Interest in software development in C++, Python and add-in based Excel
- Ability to learn new concepts, models, and technologies quickly
- Intellectual maturity and scientific curiosity are a plus
Quantitative Modeling Intern - London employer: ExodusPoint Campus
Contact Detail:
ExodusPoint Campus Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Modeling Intern - London
✨Tip Number 1
Network like a pro! Reach out to professionals in the finance and quantitative modelling space on LinkedIn. A friendly message can go a long way, so don’t be shy about asking for advice or insights into their work.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, data science, or financial modelling. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common quantitative modelling questions and be ready to discuss your thought process. We want to see how you think!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to connect directly with us. Don’t miss out on this opportunity!
We think you need these skills to ace Quantitative Modeling Intern - London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Quantitative Modeling role. Highlight relevant coursework, projects, and skills that align with the job description. We want to see how your background in STEM and data science makes you a great fit!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about quantitative modeling and how your experiences have prepared you for this internship. Let us know what excites you about working at ExodusPoint.
Showcase Your Technical Skills: Don’t forget to mention your programming skills! Whether it's Python, C++, or Excel, make sure we know what tools you’re comfortable with. If you've worked on any relevant projects, give us the details – we love seeing practical applications of your skills!
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application directly and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at ExodusPoint Campus
✨Know Your Numbers
Brush up on your quantitative skills and be ready to discuss relevant mathematical concepts. Since the role involves financial and data modelling, make sure you can explain how you would approach a problem using statistics or applied mathematics.
✨Showcase Your Coding Skills
Familiarise yourself with Python and any other programming languages mentioned in the job description. Be prepared to talk about your past projects or coursework that involved coding, and if possible, bring examples of your work to demonstrate your abilities.
✨Understand the Company’s Approach
Research ExodusPoint Capital and their multi-strategy investment approach. Understanding their business model and how the Quantitative Modeling team fits into it will show your genuine interest and help you tailor your answers during the interview.
✨Ask Insightful Questions
Prepare thoughtful questions that reflect your understanding of the role and the company. This could include inquiries about the tools they use for quantitative analysis or how the QM team collaborates with other departments. It shows you're engaged and eager to learn more.