Job Description
Role Overview:
* Drive research into short-horizon, high-frequency trading signals with typical holding periods of several hours to a few days
* Take ownership of execution and market microstructure research, helping optimize trading strategy design and implementation
* Collaborate with a cross-functional team of researchers, technologists, and portfolio managers in a highly iterative, data-driven workflow
* Build and oversee a small, high-caliber team of junior researchers (2–3 people), contributing to both leadership and hands-on research
* Leverage a modern research stack that includes distributed computing environments (e.g. AWS, Slurm), large-scale data tools (e.g. kdb+, Exasol), and advanced methods in statistics and machine learning
Ideal Candidate Will Have:
* 3+ years of experience in a quantitative trading or research role at a hedge fund, proprietary trading firm, or sell-side algo desk
* Demonstrated contributions to alpha generation or strong potential to do so in a collaborative environment
* Strong academic credentials (First Class, Honours, MSc or PhD) in a quantitative or technical field such as Mathematics, Statistics, Physics, Computer Science, Engineering, or Finance
* Familiarity with high-frequency or tick-level data and an ability to derive actionable insights from complex datasets
* Proficiency in Python or C++; experience with distributed computing and low-latency research environments is advantageous
* Strong preference for candidates with kdb+/q experience and familiarity with execution protocols such as FIX
* Confident communicator, able to clearly explain concepts, defend ideas, and work collaboratively with non-research stakeholders