Tooling
Build robust and reusable tools in Python to improve the overall team productivity.
Market Impact Modelling
Research, develop, and refine sophisticated market impact models to seek to predict and minimize the cost of trading.
Leverage large datasets and advanced statistical/machine learning techniques to improve model accuracy.
Transaction Cost Analysis (TCA)
Conduct in-depth Transaction Cost Analysis (TCA) to evaluate the performance of execution strategies, identify drivers of transaction costs, and pinpoint opportunities for optimization.
Provide actionable insights to portfolio managers and traders.
Collaboration
Work closely with the QES Lead for APAC to align strategies with regional market nuances and business objectives.
Collaborate with trading desks, technology teams, and other quantitative researchers to integrate solutions and drive innovation
What You’ll Bring
PhD/Master’s in a quantitative field (CS, Mathematics, Statistics, Physics, Engineering, Quant Finance) from a top university, with 0–4 years’ experience in quantitative research and/or development for systematic or execution strategies.
Solid Python programming skills (required), strong understanding of data structures and algorithms, and experience manipulating large-scale datasets using SQL; C/C++ is a strong differentiator.
Strong expertise in regression models, time-series analysis, and applied machine learning, with exposure to deep learning and/or reinforcement learning, ideally in data-intensive, production-oriented environments.
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