Responsibilities - Have deep understanding in modern Machine Learning methodologies, LLM and NLP techniques, and apply thoughtful quantitative, data science and analytical skills to solve complex business problems.
- Develop risk strategies that improve risk monitoring capabilities through using various source.
- Analyze structured/unstructured data from internal and external data sources to drive actionable insights in credit risk.
- Lead development of event-driven scenario analytics to analyze the impact of macro-economic factors and current events on the Wholesale portfolio.
- Develop data visualization and summarization techniques to convey key findings in dashboards and presentations to senior management.
Required Qualifications, Capabilities and Skills - Advanced degree in analytical field (e.g., Data Science, Computer Science, Engineering, Mathematics, Statistics)
- Deep understanding and practical expertise and/or work experience with Machine Learning. LLM/NLP expertise or experience is strongly preferred.
- Experience across broad range of modern analytic and data tools, particularly Python/Anaconda, TensorFlow and/or Keras/PyTorch, Spark, SQL etc. Experience working on Cloud is preferred.
- Excellent problem solving, communications, and teamwork skills.
- Financial service background or Credit Risk experience preferred, but not required.
- Desire to use modern technologies as a disruptive influence within Banking.
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