WorldQuant
Quantitative Execution Strategist
Graduate role focused on execution research and development of execution algorithms, market impact models, and transaction cost analysis using quantitative and machine learning techniques within a systematic trading environment.
Responsibilities
- Develop detailed specifications for new and enhanced execution algorithms.
- Implement, test, and deploy robust quantitative trading strategies and tools, primarily using Python.
- Build robust and reusable tools in Python to improve the overall team productivity.
- 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.
- 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.
- 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
Requirements
- 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.
Skills
- Python
- SQL
- C/C++
- Regression models
- Time-series analysis
- Machine learning
- Deep learning
- Reinforcement learning
- Employer posted
- Last checked