This team specialises in the electronic trading, leveraging advanced quantitative techniques to enhance market-making strategies and drive improvements in algorithmic trading. The ideal candidate will have strong expertise in quantitative research, coding proficiency in kdb+, Python, and Java, and a deep understanding of the e-market.
As a key member of this high-performing team, you will be responsible for conducting cutting-edge research in the market-making space. You will work on a mixture of market-making strategies, algorithmic enhancements, and alpha research to support both principal and agency trading activities. The team operates at the forefront of statistical complexity, and you will collaborate closely with traders and quants in a high-calibre research-driven environment.
Key Responsibilities:
- Market Making Strategy Development: Design and implement innovative market-making strategies, optimising pricing, liquidity provision, and execution in fast-paced, competitive markets.
- Algorithm Improvement: Work on enhancing existing algorithmic trading models and optimise their performance by incorporating novel quantitative techniques, improving execution efficiency and risk management.
- Alpha Research: Conduct in-depth research to identify new alpha signals and trading opportunities, integrating them into the trading system to improve profitability and competitiveness.
- Quantitative Analysis: Perform advanced statistical analysis, backtesting, and modelling of trading strategies, leveraging historical market data to develop actionable insights and robust models.
- Collaboration: Work closely with other quants, traders, and technology teams to integrate research findings into production systems, ensuring seamless execution of trading strategies.
- Data-Driven Decision Making: Utilise large-scale market data and real-time trading information to guide decisions, providing a quantitative basis for trade execution and strategy adjustments.
- Continuous Improvement: Contribute to the development of cutting-edge techniques and methodologies in quantitative research and algorithmic trading to maintain a competitive edge in the market.
Key Requirements:
- Experience & Expertise:
- Experience (typically 3+ years) in quantitative research or electronic trading within Rates.
- Strong knowledge of Rates market micro-structure, market-making, and trading strategies.
- Familiarity with principal and agency trading models and their application in the Rates space.
- Technical Skills:
- High-level proficiency in kdb+ (Q) and Python, with solid experience in Java.
- Strong background in statistical modelling, time series analysis, and high-frequency trading data.
- Familiarity with quantitative finance libraries, data analysis techniques, and backtesting platforms.
- Mathematical & Statistical Skills:
- In-depth understanding of advanced statistical methods, machine learning techniques, and time-series analysis as applied to quantitative trading and market-making.
- Expertise in model calibration, risk management, and optimisation techniques.
- Educational Background:
- A Master's or PhD degree in a quantitative discipline such as Mathematics, Statistics, Computer Science, Physics, Engineering, or Finance.
- Soft Skills:
- Strong analytical, problem-solving, and communication skills.
- A team player with the ability to collaborate effectively with traders, other quants, and technology teams in a fast-paced environment.
