The Wholesale Credit Risk Quantitative Research – Applied AI/ML team at the firm is looking to develop Generative AI solutions to enhance the current End-to-End credit risk process across all of Wholesale.
Requirements
- 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
- Experience with model implementation/production deployment is preferred
Responsibilities
- Have deep understanding in modern Machine Learning methodologies, LLM and NLP techniques, and apply thoughtful data science and analytical skills to solve complex business problems.
- Develop risk strategies that improve risk monitoring capabilities through the use of data from various source.
- Analyze structured/unstructured data from internal and external data sources to drive actionable insights in credit risk.
- Lead development and rapid deployment AI solutions based on 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.
Other
- Advanced degree in analytical field (e.g., Data Science, Computer Science, Engineering, Mathematics, Statistics)
- Excellent problem solving, communications, and teamwork skills
- Financial service background preferred, but not required
- Desire to use modern technologies as a disruptive influence within Banking
