At a Glance
- Tasks: Dive into quantitative research, data science, and trading while developing cutting-edge algorithms.
- Company: Join Jump Trading, a leader in innovative financial technology and research.
- Benefits: Gain hands-on experience, mentorship, and training in a dynamic environment.
- Other info: Collaborative culture with opportunities for growth and learning in a fast-paced industry.
- Why this job: Make an impact in global financial markets with your skills in math and programming.
- Qualifications: Strong background in Mathematics, Physics, or Computer Science; programming skills are a plus.
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 Trading Analyst Intern 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 Trading Analyst Intern in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Jump Trading!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Quantitative Trading Analyst Intern at Jump Trading.
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Jump Trading.
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When you find a suitable opening like Quantitative Trading Analyst Intern at Jump Trading, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Quantitative Trading Analyst Intern in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Jump Trading, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Jump Trading. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Jump Trading
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Jump Trading!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
