Design, implement, and evaluate ML models for trading; deploy to production.
Apply rigorous statistics to measure performance, control overfitting, and interpret risk.
Investigate novel ML approaches through experimentation in real trading environments.
Communicate research progress and outcomes across the team and departments.
Collaborate with traders, researchers, and engineers to translate research into production trading systems.

🎯 Requirements

Final-year student graduating in 2027.
MSc (PhD preferred) in ML, Stats, DL, probabilistic programming, or related field.
Strong foundations in statistics and ML with a research track record.
Proficiency in PyTorch and Python.
No prior finance knowledge required.
Available to start full-time February or August 2027.

🎁 Benefits

Collaborative, high-performance culture.

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