Summer Quant Research Intern Trading Floor

Summer Quant Research Intern Trading Floor

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

  • Tasks: Dive into real-world algorithmic trading problems and gain hands-on experience.
  • Company: Join Susquehanna International Group, a leader in quantitative research.
  • Benefits: Gain valuable skills, network with professionals, and enjoy a dynamic learning environment.
  • Other info: Experience a blend of classes, practical projects, and trading games in a collaborative setting.
  • Why this job: Learn from experts while working on innovative projects that shape the trading world.
  • Qualifications: Open to penultimate-year PhD and research masters students with a passion for quantitative research.

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

Susquehanna International Group in London invites penultimate-year PhD and research masters students to join a 10-week quantitative research summer internship. Learn from senior traders and researchers, working on real-world algorithmic trading problems while gaining hands-on experience with proprietary data spaces and novel modelling approaches.

The programme blends classes with practical projects and trading games.

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Summer Quant Research Intern Trading Floor employer: Susquehanna International Group

Susquehanna is an exceptional employer for graduates seeking to launch their careers in trading systems engineering. With a strong emphasis on education and continuous development, employees benefit from a collaborative and non-hierarchical culture that fosters innovation and problem-solving. Located in the heart of London, our modern office offers unique perks such as free onsite catering and a games room, making it an ideal environment for ambitious individuals to thrive.

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Contact Details:

Susquehanna International Group Recruitment Team

We think you need these skills to ace Summer Quant Research Intern Trading Floor

Quantitative Research
Algorithmic Trading
Data Analysis
Statistical Modelling
Problem-Solving Skills
Hands-on Experience
Collaboration