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Senior Manager, Asset Management


Job details
  • GCS Quant
  • London
  • 3 weeks ago
Applications closed

Quantitative Manager - Energy Trading We are mandated by a renowned energy proprietary trading firm who is seeking an experienced Quantitative Manager to lead and oversee the quantitative strategies across their energy trading desks in the European power and gas markets. This high-impact role involves developing and refining advanced models, managing a team of quantitative professionals, and ensuring our trading strategies are driven by cutting-edge data and analytic. You will be responsible for optimising performance across desks including Short-Term Stack, Carbon, and Intraday Trading. As a leader, you will collaborate closely with traders, analysts, and technical teams to drive innovation, improve performance, and strengthen the firm's competitive edge in a rapidly evolving market. If you are passionate about quantitative analysis, energy markets, and team leadership, we want to hear from you. Drive model integration into trading platforms, ensuring real-time execution and actionable insights to maximise trading performance. Manage and mentor a high-performing quant team, fostering collaboration across trading desks and driving continuous professional growth. Advance power market models using statistical and machine learning techniques to improve trading strategies and decision-making. Oversee back testing and automation of trading strategies using trade/order book data and financial time series analysis. Identify and exploit market inefficiencies, developing pricing models for options, OTC instruments, and physical assets. Support strategies for liquid assets, capturing value in less-liquid market segments. Evaluate performance of quantitative tools and strategies, driving improvements through KPIs like Return on Collateral (RoC) and trading metrics. Strong experience leading teams and managing cross-functional projects. Advanced proficiency in statistical modelling, optimisation (LP, MILP), and time series analysis. Expert-level programming skills in Python, SQL, and NoSQL; Familiarity with machine learning techniques in trading environments is highly desirable. In-depth understanding of EU power and gas markets (knowledge of Japan markets is a plus). Strong background in market data analytic, including trade/order book data and financial market structures.

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