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Commodity Trading Data & AI Specialist

Job in Genf, Geneva, Switzerland
Listing for: Direction employeurs
Full Time position
Listed on 2026-10-04
Job specializations:
  • IT/Tech
    Data Scientist, Data Analyst, Machine Learning/ ML Engineer, AI Business & Operations
  • Finance & Banking
    Data Scientist, AI Business & Operations
Salary/Wage Range or Industry Benchmark: 120000 - 190000 CHF Yearly CHF 120000.00 190000.00 YEAR
Job Description & How to Apply Below
Location: Genf

Commodity Trading Data & AI Specialist

About the Role :

Commodity Trading Company based in Geneva is seeking a highly analytical and technically skilled Data & AI Specialist with a strong interest in physical commodity trading, artificial intelligence, and advanced analytics.

The successful candidate will support Trading, Finance, and Operations teams by transforming commercial, operational, and financial data into actionable insights, analytical tools, and AIpowered solutions.

The role combines commodity trading analysis, data analytics, machine learning, and generative AI applications to improve decision-making, profitability analysis, operational efficiency, and digital transformation within the Company.

The position is ideal for a candidate with a strong quantitative background, excellent programming skills, and the ability to bridge business requirements with advanced data and AI solutions.

Main Responsibilities
  • Commodity Trading Analytics :

    Analyze physical commodity trading activities, including contracts, pricing terms, payment conditions, operational requirements, and trade performance.

    Extract and structure key commercial information from trading documentation to support business analysis.

    Calculate and analyze trader margins, profitability indicators, commercial KPIs, and performance metrics.

    Perform statistical analysis on trading activities to identify profitability drivers, execution risks, market trends, and improvement opportunities.

    Support Trading teams with data-driven insights and analytical tools.
  • Data Analytics & Business Intelligence :

    Collect, clean, standardize, and analyze trading, operational, and financial datasets.

    Develop analytical models to improve visibility on trading performance, profitability, and operational efficiency.

    Build reporting tools, dashboards, and analytical solutions for Trading, Finance, Operations, management, and shareholders.

    Transform complex datasets into clear and actionable business insights.
  • Artificial Intelligence & Machine Learning Solutions :

    Identify and develop AI use cases supporting trading, finance, and operational processes.

    Design and implement machine learning models for predictive analytics, forecasting, anomaly detection, and decision support.

    Develop AI-powered applications using structured and unstructured business data.

    Build and evaluate Generative AI solutions, including Large Language Models (LLMs),Retrieval-Augmented Generation (RAG), and intelligent assistants.

    Automate analytical workflows and improve access to business information through AI solutions.
  • Data Preparation & AI Readiness :

    Prepare and structure data assets required for analytics and AI applications.

    Improve data quality, consistency, and accessibility across business functions.

    Support the development of reliable datasets for machine learning and advanced analytics.
  • Innovation :

    Monitor developments in artificial intelligence, machine learning, and data science relevant to commodity trading.

    Evaluate emerging technologies and identify opportunities to improve trading and operational processes.

    Contribute to the Company’s AI roadmap and digital transformation initiatives.
Required Qualifications
  • Master’s degree in Data Science, Computer Science, Statistics, Applied Mathematics, Quantitative Finance, or a related quantitative field.
  • Experience or strong interest in physical commodity trading, financial markets, or commercial analytics.
  • Strong programming skills in Python and SQL.
  • Experience with data analysis, statistical modelling, and machine learning techniques.
  • Experience developing predictive models or AI applications using financial, commercial, or market data.
  • Practical knowledge of Generative AI technologies, Large Language Models (LLMs), or machine learning…
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