At a Glance
- Tasks: Collaborate with Quantitative Developers on exciting trading projects using Python and C++.
- Company: Xantium, a leading firm in quantitative trading with offices in London and New York.
- Benefits: Gain hands-on experience, mentorship, and exposure to cutting-edge technology.
- Other info: Perfect opportunity for aspiring developers looking to kickstart their careers.
- Why this job: Join a dynamic team and make an impact in the fast-paced world of trading.
- Qualifications: Must be in your penultimate year studying Computer Science.
The predicted salary is between 22500 - 27500 £ per year.
Xantium is seeking Quantitative Developer Interns for our London and New York offices for Summer 2027. Candidates must be in their penultimate year, studying Computer Science.
Quantitative Developer Interns will work closely with our team of Quantitative Developers and Researchers on projects powering our quantitative trading.
Our tech stack is a blend of Python and C++ that runs both on-prem and in the cloud.
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Quantitative Trading Intern - Python & C++ employer: Xantium
Xantium is an exceptional employer for Quantitative Volatility Traders, offering a dynamic work environment in the heart of New York City. With a strong emphasis on collaboration, employees benefit from mentorship opportunities that foster professional growth and development in trading strategies. The competitive compensation package, including guaranteed bonuses, reflects our commitment to rewarding talent and performance, making Xantium a prime choice for those seeking a meaningful career in finance.
StudySmarter Expert Advice🤫
We think this is how you could land Quantitative Trading Intern - Python & C++
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We think you need these skills to ace Quantitative Trading Intern - Python & C++
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!
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✨Brush Up on Your Statistics
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✨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.
