Quantitative Trading Off-Cycle Intern
London, England, United Kingdom
Onyx Capital Group
Onyx provides expert services for pro traders and newcomers, levelling the playing field across the oil derivatives space.Onyx Capital Group was founded, by traders, on the principles of expertise, vision and excellence. The company has rapidly grown to command across the entire spectrum of oil derivative products. Our aim is not just to be market leaders but to build a unique franchise that continuously pushes boundaries. We know that our success is derived from a total commitment to pursue excellence in both our people and our technology which we heavily invest in.
We are currently hiring for a number of interns with strong quantitative skills to join our Systematic Trading team. This role would be offered on a 3 month basis initially, with potential for extension.
Your future role within Onyx would include:
- Supporting with high quality systematic strategies in production
- Monitoring continuous trading, strategy performance and all relevant risks
- Implementing signals and relevant datasets within the global execution platform
- Monitoring signal behaviour and performance of execution platform over time
- Supporting the full-strategy trading cycle from risk calibration to trade executions
Requirements
- Bachelors or Masters degree in a quantitative field such as computer science, statistics, mathematics, physics, or engineering
- Knowledge of statistics and Machine Learning
- Capacity to multi-task in a fast-paced environment while keeping strong attention to detail
- Python skills/experience desirable
- Experience in exploring large datasets across multiple time frames
- Curiosity about global energy and commodities markets
- Intellectual curiosity to explore new data sets, solve complex problems, drive innovative processes, and connect the dots between multiple fields
- Capacity to work with autonomy within a collegial and collaborative environment
- Good communication skills
Tags: Computer Science Engineering Machine Learning Mathematics Physics Python Statistics
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