Algo Quant Researcher - Rates Swaps


London
Permanent
Negotiable
Financial Technology
PR/561820_1758553852
Algo Quant Researcher - Rates Swaps

Our client is seeking a Quant Researcher to join their Electronic Market Making team within the Statistical Modelling and Development group at a leading investment bank in London. This is a business-critical role focused on algorithmic research and trading of Rates Swaps, primarily Dollar and Euro, with increasing exposure to Sterling.

As an Algo Quant, you'll work in a highly collaborative and intellectually stimulating environment, partnering closely with Principal Trading and Quant Development teams. You'll drive the research and deployment of systematic market making and position-taking strategies, leveraging advanced quantitative methods and a robust Python/Java technology stack.

Responsibilities:

  • Research and develop systematic market making and position-taking strategies for Rates Swaps (USD, EUR, GBP).
  • Analyse large and complex datasets to identify Alpha signals, market inefficiencies, and microstructure patterns.
  • Design and implement robust statistical models and algorithms for real-time trading.
  • Backtest and validate strategies using historical and live market data.
  • Monitor, analyse, and optimise live trading performance, identifying areas for improvement.
  • Collaborate with traders, quants, and technologists to translate business objectives into quantitative solutions.
  • Present research findings and strategy performance to senior stakeholders.

Requirements:

  • 5+ years of experience in quantitative research or systematic trading, ideally within Rates, Fixed Income, or Derivatives.
  • Deep understanding of Rates Swaps markets (USD, EUR, GBP) and electronic trading workflows.
  • Advanced quantitative skills (mathematics, statistics, econometrics, or related field).
  • Strong programming skills in Python; familiarity with Java-based infrastructure.
  • Proven experience developing and deploying systematic trading strategies.
  • Experience with large-scale data analysis, backtesting, and performance attribution.
  • Excellent communication and collaboration skills.
  • High motivation, intellectual curiosity, and a passion for financial markets.

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