Machine Learning Strategist – Systematic Commodities

vor 6 Stunden

Zürich, Schweiz Altus Search Ltd Vollzeit

Senior Machine Learning Strategist – Systematic Commodities Title: Senior Machine Learning Strategist – Systematic Commodities Date: 12th December 2025 Our client, a global financial institution, is seeking a Machine Learning Strategist to join their commodities division. This position is ideal for a candidate with a strong foundation in quantitative methods and a passion for building advanced analytics solutions that support commodity trading and management. In this role, you will define strategic priorities, streamline workflows, and apply sophisticated data science techniques to enhance decision‑making. Responsibilities Design and implement machine learning models to anticipate commodity price movements Analyse macroeconomic indicators, supply chain disruptions, and geopolitical inputs to inform strategy Partner with external analytics vendors to integrate advanced modelling tools Build, enhance, and maintain Azure and Databricks data pipelines, ensuring data accuracy, timeliness, and scalability. Monitor and enhance model performance, expanding scope as needed. Build feature pipelines and automate data workflows for real‑time signal generation Present insights and model outputs directly to trading desks and investment leads Qualifications The preferred candidate should possess experience working with Python code and strong knowledge of DevOps practices (e.g., Git, Agile methodology), Azure, and Databricks. Excellent communication and interpersonal skills are essential and the ability to interact at all levels of business efficiently is required. Solid foundation in supervised/unsupervised learning, NLP, and time‑series forecasting. Contact If you are interested in this opportunity, please email your C.V. to contact@altussearch.ch or call Altus Search on +41 (0) 41 560 02 21 for a confidential discussion. Seniority level Mid‑Senior level Employment type Full‑time Job function Finance and Information Technology #J-18808-Ljbffr

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