Quantitative Derivatives Researcher β€” Trading Team

Quantitative Derivatives Researcher β€” Trading Team

Full-Time 63000 - 77000 Β£ / year (est.) No working from home possible
P2P

At a Glance

  • Tasks: Use maths and machine learning to predict market signals in global derivatives.
  • Company: Join Jump Trading Group, a leader in innovative trading solutions.
  • Benefits: Competitive salary, flexible work hours, and opportunities for professional growth.
  • Other info: Dynamic team environment with a focus on innovation and collaboration.
  • Why this job: Make an impact by collaborating with top traders and researchers in live trading.
  • Qualifications: Advanced degree in a quantitative field and strong Python/C++ skills required.

The predicted salary is between 63000 - 77000 Β£ per year.

Jump Trading Group seeks a highly skilled quantitative researcher to apply mathematics, statistics, and machine learning to identify patterns and predict market signals across global derivatives. You will collaborate with traders, researchers, and engineers to push innovative ideas and implement them in live trading environments.

Ideal candidates hold an advanced degree in a quantitative field, have strong Python and C++ development skills, and demonstrate a track record of developing.

Quantitative Derivatives Researcher β€” Trading Team employer: P2P

P2P is an exceptional employer that fosters a dynamic work culture focused on innovation and collaboration in the heart of Greater London. With a commitment to employee growth, we offer extensive professional development opportunities and a supportive environment for those passionate about advancing decentralized finance. Join us to be part of a forward-thinking team that values your contributions and encourages meaningful impact in the financial services sector.

P2P

Contact Details:

P2P Recruitment Team

We think you need these skills to ace Quantitative Derivatives Researcher β€” Trading Team

Mathematics
Statistics
Machine Learning
Python
C++
Pattern Recognition
Market Signal Prediction