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    Fundamental Commodities Modelling Lead - London, United Kingdom - Millennium Management

    Millennium Management
    Millennium Management London, United Kingdom

    1 week ago

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    Description
    Fundamental Commodities Modelling Lead

    Millennium is a top tier global hedge fund with a strong commitment to leveraging innovations in technology and data science to solve complex problems for the business. We are assembling a strong Quant Technology team to build our next generation in-house analytics and trader support tools. This team will sit under the Fixed Income & Commodities Technology (FICT) group and will develop and maintain the in-house pricing libraries to support trading in Fixed Income, Commodities, Credit, and FX business at Millennium. FICT provides a dynamic and fast-paced environment with excellent growth opportunities.

    Responsibilities:

  • Newly created role to build data science-inspired models for forecasting a wide range of variables driving commodities fundamentals, such as power and natural gas demand, production capacities, inventory levels, pipeline and transmission line congestion, refinery outages, etc.
  • Both statistical and causal model types are in scope, so that regressions, time series analysis, and supply-demand balancing models such as power stack models are all involved.
  • Overseeing and mentoring junior fundamentals analysts.

    • Requirements:

  • Minimum of 5 years of experience with modeling commodities fundamentals in at least one area such as European power and gas, US power and gas, global oil, or ags and softs.
  • An intimate knowledge of handling, cleaning and organizing data is required. This includes familiarity with data sources and providers for temperature, load, rainfall and other related inputs, as well as the structure and methodology of forecasts available from third-party vendors.
  • Practical knowledge of python and an associated tool stack for data science is essential.
  • Previous experience leading/supervising a team beneficial
  • Knowledge of valuation, pricing and derivatives models is useful but not required.
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