Quant Trade Researcher

About the role

AlgoQuant Asset Management is seeking Quant Trade Researchers to design, test and deploy systematic trading strategies for digital asset markets. Reporting to the Head of Research, you will work alongside portfolio managers and engineers to move ideas from concept to live capital quickly.

Key responsibilities

• Generate and test systematic trading hypotheses across spot, derivatives and on‑chain markets.
• Build, validate and maintain live alpha signals and execution models.
• Run rigorous backtests while guarding against look‑ahead bias, data leakage and over‑fitting.
• Analyse micro‑structure, order‑flow and cross‑venue dynamics to improve portfolio construction.
• Collaborate with engineers to transition research from notebooks to production systems.
• Monitor live strategy performance and iterate rapidly based on results.
• Contribute to shared research infrastructure, tools, datasets and code bases.

Required profile

• Exceptional mathematical, statistical or scientific pedigree (Olympiad medallists, PhDs or top‑decile graduates in maths, physics, computer science, etc.).
• Deep understanding of statistical learning, classical machine learning and deep learning.
• Strong programming ability, Python required; C++ or Rust a plus.
• Relentless curiosity, high agency and comfort owning research end‑to‑end.
• For junior candidates: demonstrable research potential (papers, Kaggle wins, competitive programming, systematic trading experiments).
• For senior candidates: a live, attributable track record in systematic trading.

Required skills

• Python
• C++
• Rust
• Statistical learning
• Machine learning
• Deep learning
• Boosting algorithms
• Transformers
• Reinforcement learning
• Backtesting
• Data analysis
• Micro‑structure analysis