Quantitative Risk Management Analyst

Office Montreal, QC
Status Full time - Permanent
The Quantitative Analyst will play a key role by working closely with the risk management team to support the operation and development of the department. Their contribution will be essential in optimizing the use of various industry data, significantly impacting risk management. Their input will be crucial in achieving our company's ambitious goals in the North American market, all from our offices located in the heart of Montreal. As a Quantitative Analyst, you will be responsible for assessing the risks associated with all of the company's products. You will also be in charge of overseeing the evaluation of data providers and managing these data.
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Your daily life at MAG
  • Conduct quantitative and qualitative analyses using advanced statistical and probability methods for decision-making and understanding energy price movements.
  • Propose, develop, and revise machine learning models, stochastic models, and interpretability techniques for energy pricing and risk management.
  • Organize and monitor the performance of data from external suppliers.
  • Develop, review, and recommend processes and metrics (VaR, ES, Stress-Test…) to ensure that the transactional risks of different departments are in compliance with the company’s risk policy.
  • Manage data integrity and develop forecasts.
  • Communicate your findings or progress to teams and management.
  • Regularly monitor risk reports.
  • Participate in the risk management committee.
Qualities needed for success
  • Demonstrate great versatility in mathematical modeling.
  • Interest in risk management and the energy sector.
  • Possess scientific rigor and critical thinking.
  • Balance well between teamwork and autonomy.
  • Have a spirit of initiative and enjoy discussing ideas.
  • Experience in quantitative analysis with advanced statistics and probabilities (academic or professional).
  • Experience in quantitative analysis with machine learning (academic or professional).
  • Successfully completed a Master’s degree in mathematics, statistics, quantitative finance, financial engineering, data science, engineering, or another related field.
Your ecosystem
  • Python
  • SQL
  • Matlab

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