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Job Description
Structured overview of role & requirementsAbout This Role
Support and operate global credit risk reporting and analytics for Shell Trading & Supply (T&S), addressing risk management for regulatory compliance and value enhancement.
Develop and execute analytical models including Potential Future Exposure (PFE), Expected Credit Loss (ECL), Credit Value Adjustment (CVA), and portfolio analytics, with responsibility for data visualization and documentation controls.
Collaborate globally with commercial teams, credit risk managers, IT, and other stakeholders to enhance risk data integration, conduct training, and support transformation projects.
Minimum Requirements
At least 5 years of relevant work experience in analytics or risk management context.
Hands-on expertise in Python programming and machine learning frameworks such as scikit-learn, XGBoost, and data science libraries (pandas, numpy, scipy).
Practical experience using AI/ML techniques for predictive modeling, classification, anomaly detection, or NLP.
Experience with database programming, data engineering, and data transformation; knowledge of data visualization tools (Power BI, Spotfire, QlikSense) preferred.
Ideal Candidate Profile
Strong domain knowledge in credit risk analytics within energy trading or financial risk environment, capable of handling complex regulatory and operational risk reporting.
Experienced in cross-functional collaboration across multiple regions with ability to train users and support multiple stakeholders globally.
Technically adept with data modeling, automation, and orchestration tools (preferably Apache Airflow, Azure Data Factory) aiming to embed MLOps and data mesh architecture principles.