ML Engineer to Quant Researcher: math, stats, and real markets

About the role

Research systematic trading signals, models, and execution-aware hypotheses, and design robust experiments that avoid leakage and account for assumptions. Stress-test research across market regimes, costs, slippage, edge decay, and failure modes, then build reproducible pipelines and work with engineering and trading teams to productionize validated ideas. Candidates should have at least three years of experience in machine learning engineering, applied science, or research, with strong statistical reasoning and solid Python skills. They should be able to work with messy real-world datasets, build reliable pipelines, identify bias and overfitting, and communicate research outcomes clearly.