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Join our dynamic Wholesale Credit Risk Quantitative Research team as a Gen AI Data Scientist, where you'll have the opportunity to revolutionize the credit risk process using cutting-edge Generative AI solutions. This role offers a unique chance to leverage the firm's extensive big data resources and make a significant impact on the financial industry. Be part of a team that values innovation and collaboration, and help shape the future of credit risk management. As a Gen AI Data Scientist in the Wholesale Credit Risk Quantitative Research Applied AI/ML team, you will play a pivotal role in developing Generative AI tools to enhance the End-to-End credit risk process across Wholesale. You will work closely with a team that thrives on innovation and is committed to improving risk monitoring capabilities through advanced data science techniques. Job Responsibilities Develop and apply modern Machine Learning methodologies, LLM, and NLP techniques to solve complex business problems. Create risk strategies that enhance risk monitoring using data from various sources. Analyze structured and unstructured data from internal and external sources to drive actionable insights in credit risk. Lead the development and rapid deployment of AI solutions based on macro-economic factors and current events affecting 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 an analytical field (e.g., Data Science, Computer Science, Engineering, Mathematics, Statistics). Deep understanding and practical expertise in Machine Learning, with strong LLM/NLP expertise or experience. Experience with a broad range of modern analytic and data tools, particularly Python/Anaconda, Tensorflow, Keras/PyTorch, Spark, SQL, etc. Experience with model implementation and production deployment. Excellent problem-solving, communication, and teamwork skills. Desire to use modern technologies as a disruptive influence within Banking. Preferred qualifications, capabilities, and skills Experience working on Cloud platforms. Financial service background. Strong preference for candidates with experience in deploying AI solutions in a financial context.

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