At a Glance
- Tasks: Dive into research, develop algorithms, and collaborate with trading teams.
- Company: Jump Trading, a leader in innovative financial research and technology.
- Benefits: Hands-on training, mentorship, and exposure to cutting-edge technologies.
- Other info: Ideal for students from French schools seeking M1/M2 internship experience.
- Why this job: Make an impact in finance while enhancing your skills in a dynamic environment.
- Qualifications: Strong programming and quantitative analysis skills; passion for learning.
The predicted salary is between 22500 - 27500 £ per year.
Jump Trading is committed to world class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incentivising collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organisations and universities to solve problems. We build predictive models from big data and develop algorithms to automatically execute trades in dozens of financial exchanges around the world. At Jump you will have the opportunity to contribute in a blend of three roles – quant researcher / data scientist, trader, and software developer – based on your incoming skills and background, interest and curiosity, and the new skills and industry knowledge that you will learn at Jump. As an M1/M2 research intern, you’ll first undertake an intensive research project, during which time you’ll work closely with a mentor from one of our trading teams. Possible research topics are varied and can be tailored to suit specific interests or academic requirements. Then, you enter into a hands-on training program focused on enhancing your knowledge of trading, programming, and quantitative analysis. The training consists of in-house courses and trading simulation developed and delivered by our own experienced researchers, traders, and developers. Topics include Machine Learning, trading / market mechanics, C++, statistics, and our research process for signal generation During each rotation you’ll work on a project with the trading team while being mentored by experienced quant researchers, traders, and developers. This program is specifically designed for students from French schools that require the completion of the M1/M2 research internship (e.g. Ideal candidates have a strong drive to learn and improve, an entrepreneurial spirit, and strong skills in programming and/or quantitative analysis (statistics, data mining, mathematics, machine learning, etc.). We’ll give you the training that you’ll need. Although we strongly value training in Computer Science and Mathematics, we are excited to meet people with exceptional achievements in any technical discipline. Recent hires include students from fields such as Electrical Engineering, Statistics, Physics, Neuroscience, Materials Science, Operations Research, and more. If you have outstanding skills in math and programming and you are curious about the challenge of improving research with daily feedback from competitive markets, we hope you’ll apply.
Quantitative Analyst Internship in London employer: Jump Trading
Jump Trading is an exceptional employer that fosters a culture of innovation and collaboration, making it an ideal place for aspiring quantitative traders. With a focus on empowering talent through intensive training and mentorship, interns will gain hands-on experience in developing predictive models and automated trading strategies while working alongside industry experts. Located in a dynamic environment, Jump offers unique opportunities for personal and professional growth, ensuring that every team member can thrive and contribute to groundbreaking research in financial markets.
StudySmarter Expert Advice🤫
We think this is how you could land Quantitative Analyst Internship in London
✨Join Data-Science Meetups
Get yourself along to local data-science meetups or workshops. They're goldmines for networking, and you'll learn from industry pros who might just point you in the direction of internships. Plus, discussing the latest trends with like-minded individuals can really amp up your game.
✨Utilise University Career Services
Check in with your uni's career services since they often have connections with companies looking for interns. They might even organise information sessions with firms, which can be a great chance for you to learn more about potential internships and make some key contacts.
✨Show Off Your Stuff on GitHub
If you're into data science, having a GitHub profile with your projects is essential. Make sure your portfolio is public and showcases your best work! Recruiters love to see your coding skills and problem-solving approach, and it’s a brilliant way to stand out.
✨Apply Directly on Our Website
Don’t forget to check out the internships listed on our site! It's always a good idea to apply directly through our website because it makes your application easier for our team to find, and you might just catch the hiring manager’s eye by showcasing exactly what you're passionate about in data science.
We think you need these skills to ace Quantitative Analyst Internship in London
Some tips for your application 🫡
Show Off Your Technical Skills:For a data science internship, we want to see those analytical skills shine! List your programming languages, like Python or R, and make sure to highlight any relevant projects or courses you've completed. If you've dabbled with tools like Pandas, NumPy, or machine learning algorithms, don’t hold back – include those in your CV!
Share Your Curiosity in Your Cover Letter:As an intern, your motivation and eagerness to learn are key! In your cover letter, talk about specific data science concepts that excite you and how this internship at Jump Trading will help you grow. Share what you hope to achieve and how you plan to tackle real-world data problems - we love enthusiasm!
Include Any Relevant Certifications:If you've earned any certifications, such as from Coursera or DataCamp, make sure to include these in your application. They show us that you're proactive and committed to expanding your data science skillset. This could make a real difference in how we assess your application!
Keep It Relevant and Concise:Remember, as an intern, you don’t need to have decades of experience. Focus on showcasing relevant coursework, personal projects, or even related volunteer work in data science. Keep your CV and cover letter concise but impactful – we appreciate clear and straightforward communication!
How to prepare for a job interview at Jump Trading
✨Brush Up on Your Coding Skills
As a data science intern, you might get grilled on your programming skills. Expect to tackle some coding challenges using languages like Python or R. We recommend practising basic algorithms or data manipulation tasks so you can show off your tech skills with confidence.
✨Show Off Your Projects
Prepare to discuss any projects you’ve done, whether in your studies or on your own time. Having a strong portfolio of data analyses or machine learning models will really set you apart. We can use platforms like GitHub to showcase your work to impress Jump Trading.
✨Know Your Stats and ML Basics
Brush up on your statistics and machine learning concepts because interviewers love to dig into this! Be ready to explain your understanding of algorithms or how you would approach a given data problem. This will highlight your theoretical background alongside your practical skills.
✨Be Eager to Learn and Adapt
Internships are all about potential and growth. Make sure you convey your eagerness to learn and adapt to new tools or methodologies. Show Jump Trading that you’re not just looking for experience, but that you're keen to contribute and grow within the team.
