Role Overview:

1. Drive research into short-horizon, high-frequency trading signals with typical holding periods of several hours to a few days
2. Take ownership of execution and market microstructure research, helping optimize trading strategy design and implementation
3. Collaborate with a cross-functional team of researchers, technologists, and portfolio managers in a highly iterative, data-driven workflow
4. Build and oversee a small, high-caliber team of junior researchers (2–3 people), contributing to both leadership and hands-on research
5. 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:

1. 3+ years of experience in a quantitative trading or research role at a hedge fund, proprietary trading firm, or sell-side algo desk
2. Demonstrated contributions to alpha generation or strong potential to do so in a collaborative environment
3. 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
4. Familiarity with high-frequency or tick-level data and an ability to derive actionable insights from complex datasets
5. Proficiency in Python or C++; experience with distributed computing and low-latency research environments is advantageous
6. Strong preference for candidates with kdb+/q experience and familiarity with execution protocols such as FIX
7. Confident communicator, able to clearly explain concepts, defend ideas, and work collaboratively with non-research stakeholders