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Quantitative Analyst - Energy FinTech

Quantitative Analyst – Python, Machine Learning, Neural Networks, Time Series Analysis, Bayesian theory, Energy, Commodities

Energy and Commodities FinTech Business. London.

Highly Competitive + Benefits + Bonus

A growing Energy and Commodities FinTech business is looking to hire a Quantitative Analyst with experience in Python and putting machine learning concepts into a practical analytics environment.

As the Quantitative Analyst (Python, Machine Learning, Energy) you will be working on a commodities analytics systems that uses Machine Learning to predict energy usage. You will be developing your models using Python and will be working with large data sets using time-series analysis. You need to have experience deploying these concepts in a real life application and will be comfortable with the practical applications of them.

The team itself are responsible for building and optimising the quantitative models for an analytics platform that is cloud based and others a very different way for firms to manage their energy requirements. The firm is growing, with a current head count of 35, so they are looking for someone who wants to do something a bit different. It’s a great opportunity for someone who wants to break into Fintech and move away from the traditional banking environment.

The Quantitative Analyst (Python, Machine Learning, Energy) will need:

  • Experience developing models using Python – Essential
  • Experience with machine concepts (neural networks, Bayesian theory etc) – Essential
  • Experience working with large data-sets -  Highly Beneficial
  • Experience with time-series analysis – Highly Beneficial

Please get in touch with tom.kemp@harringtonstarr.com for more information.

Quantitative Analyst – Python, Machine Learning, Neural Networks, Time Series Analysis, Bayesian theory, Energy, Commodities