Summer Quant Research & Trading Internship

Summer Quant Research & Trading Internship

Internship 22500 - 27500 Β£ / year (est.) No working from home possible
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At a Glance

  • Tasks: Build models, research market behaviour, and enhance trading strategies in a hands-on role.
  • Company: XY Capital, a dynamic firm focused on quantitative research and trading.
  • Benefits: Gain real-world experience, mentorship, and networking opportunities in finance.
  • Other info: Collaborative team environment with a focus on rigorous research methods.
  • Why this job: Dive into the world of trading and make an impact with your analytical skills.
  • Qualifications: STEM students with Python proficiency and a passion for finance.

The predicted salary is between 22500 - 27500 Β£ per year.

XY Capital is seeking driven STEM students for a 10-week internship with a hands-on role in building models, researching market behavior, and enhancing trading strategies.

You will collaborate with Traders and Quant Researchers to identify alpha and execute models across asset classes.

The program emphasizes rigorous research methods, Python proficiency (Pandas, Sci-Kit Learn, XGBoost, Tensor Flow), and a team-based environment.

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Summer Quant Research & Trading Internship employer: Trading Interview

Virtu Financial is an exceptional employer that fosters a dynamic and meritocratic work environment, perfect for those looking to kick start their career in financial technology. With generous benefits such as 26 days of annual leave, comprehensive health coverage, and a strong emphasis on employee well-being, Virtu prioritises both professional growth and personal fulfilment. The collaborative culture encourages innovation and teamwork, making it an exciting place to thrive while contributing to cutting-edge solutions in global markets.

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Contact Details:

Trading Interview Recruitment Team

We think you need these skills to ace Summer Quant Research & Trading Internship

Python Proficiency
Pandas
Sci-Kit Learn
XGBoost
TensorFlow
Quantitative Research
Model Building