Job Description
Position
This role will be part of the Wholesale Credit Risk Quantitative Research – Applied AI/ML team that has been tasked to develop Generative AI solutions on top of the firm’s big data resources. In particular, the role will focus on building tools based on LLM to enhance the current End-to-End credit risk process across all of Wholesale.
Responsibilities Include but not limited to:
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.
Qualifications
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
Experience with model implementation/production deployment is preferred
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
This role will be part of the Wholesale Credit Risk Quantitative Research – Applied AI/ML team that has been tasked to develop Generative AI solutions on top of the firm’s big data resources. In particular, the role will focus on building tools based on LLM to enhance the current End-to-End credit risk process across all of Wholesale.
Responsibilities Include but not limited to:
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.
Qualifications
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
Experience with model implementation/production deployment is preferred
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
💡 Quick Summary
Seeking a career-building opportunity? The Gen AI Data Scientist - Wholesale Credit Risk position is now open for candidates interested in the Database Administrator sector. This role in Mumbai offers a professional environment and growth potential.
Requirement Snapshot: Candidates should possess basic communication skills, a proactive attitude, and the ability to work in a team. Experience in Database Administrator is a plus.
