Senior Data Scientist - Commodity Trading And Risk Management

About the Role As a member of the Commodity Analytics team, you will be based in one of the following offices: Brussels, Amsterdam, Madrid, or Lisbon.
You'll work closely with McKinsey's Commodity Trading Service Line to support clients across sectors and geographies.
Responsibilities Support commodity producers, processors, buyers, and traders across agriculture/softs, metals, energy, and consumer sectors to improve commodity price risk capabilities with cutting-edge data science.
Collaborate with the Commodity Trading Service Line to assist clients in commodity trading and risk strategy, trading operations transformation, and trading and risk digitization.
Work with client service teams to address pressing issues using an analytical approach and communicate findings to executive audiences.
Build innovative algorithms and products for client needs, from price forecasting models to new offers and solutions.
Apply advanced analytics to enhance commodity risk management decisions through model maintenance, algorithm improvements, and risk management strategy testing.
Qualifications An undergraduate degree is required; an advanced degree in a quantitative discipline is preferred.
You should have 2+ years of commodity markets experience, proficiency in Python coding, and the ability to apply analytical methods to solve business problems in commodity markets.
Additional Requirements You should be able to explain commodity market nuances to non-specialists, work with version control and Agile methodology, and have experience in developing trading or hedging strategies.
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