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Chennai metro and broad ML/GCP/SAS skillset increase applicant competition.
Strong banking credit risk domain expertise required, making cross-industry transferability limited.
Requires advanced degree plus mandatory GCP, SAS, R, Python and credit risk modeling expertise.
Design, build, and deploy Generative AI tools and Large Language Model (LLM) applications to support credit risk modelers and enhance efficiency.
Develop and validate credit risk models using GCP, SAS, R, and Python, delivering actionable insights to improve business outcomes.
Lead AI infrastructure development for risk analytics, ensuring data privacy, security, and compliance in all AI tools and solutions.
Masters degree in Finance, Financial Engineering, Analytics, Mathematics, Computer Science, Statistics, Industrial Engineering, Operations Research, or related field.
Proven hands-on experience in Artificial Intelligence and extensive experience with Google Cloud Platform (GCP).
Strong knowledge of credit risk modeling techniques including Probability of Default (PD), Loss Given Default (LGD), and Exposure At Default (EAD).
Programming skills in GCP, R, SAS, and Python; proficiency with Excel, PowerPoint, and Word. Work Experience Required: Not explicitly mentioned in the JD.
Experienced in applying predictive modeling and statistical methodologies for credit risk quantification and validation in financial contexts.
Able to translate technical AI and modeling solutions to practical workflows and collaborate closely with quantitative analysts and modelers.
Familiarity or experience with cloud-based analytical solutions development, especially using GCP, and adherence to strict data governance and security standards.