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Tier-1 employer, mid-level generalist data role in Bangalore with broad required skills increases applicant competition.
Role requires trading credit risk domain knowledge and ETRM experience, limiting cross-industry transferability.
Mandatory 5+ years, Python/ML, data engineering and risk-domain expertise enforce strict shortlisting.
Lead development and operation of global credit risk reporting and analytics for Shell Trading & Supply, supporting commercial and risk management teams worldwide.
Create and enhance credit risk analytics including Potential Future Exposure, Expected Credit Loss, Credit Value Adjustment, and portfolio analytics to influence financial reporting and decision-making.
Develop data visualizations, maintain documentation and controls, train users, and collaborate with cross-functional teams including IT, Commercial, and Risk to ensure effective credit risk management.
At least 5 years of relevant experience in data analytics with practical application of AI/ML techniques in risk or analytical contexts.
Strong Python skills including libraries such as scikit-learn, XGBoost, pandas, numpy, scipy, with database programming and data transformation experience.
Experience with credit risk analytics concepts such as PFE, ECL, CVA, and portfolio credit analytics.
Knowledge of data visualization tools (e.g., Power BI, Spotfire) and orchestration tools (e.g., Apache Airflow, Azure Data Factory) preferred but not mandatory.
Experienced analytics professional with working knowledge of AI/ML applied specifically in credit risk or financial risk management within a global trading environment.
Capable of integrating business understanding with data modeling to deliver robust credit risk analytics and reporting globally across multiple regions.
Skilled in developing user training, documenting processes, and collaborating across IT, Commercial, and Risk teams to enhance operational risk management capabilities.