Credit Risk Modeling Role - Gen AI - Risk Analytics CoE - Risk & Regulatory Practice

Credit Risk Modeling- Gen AI

Experience level: 26 years of relevant experience

Location: Bangalore

About the Team

The Risk Analytics Center of Excellence (CoE) is an integral part of Risk and Regulatory (R&R) practice, delivering advanced quantitative risk solutions to global banks and financial institutions. Our team is composed of highly skilled professionals with deep expertise across credit risk modeling, AI/ML development, model validation, and regulatory compliance. We apply a combination of traditional statistical approaches and advanced AI/ML techniques to solve complex risk challenges across portfolios and geographies.

Role Overview

We are looking for high-caliber professionals with strong foundations in credit risk modeling and hands-on experience in AI/ML techniques. The ideal candidate will contribute to the development and validation of regulatory and strategic risk models, while also applying machine learning and generative AI techniques to enhance model accuracy, efficiency, and interpretability.

Key Responsibilities

- Develop, validate, and document credit risk models (PD, LGD, EAD) for retail and wholesale portfolios across regulatory (CECL, IFRS 9, Basel) and business-use contexts.

- Apply AI/ML algorithms (e.g., LightGBM, XGBoost, Random Forest, Neural Networks) to improve prediction power and model performance beyond traditional approaches.

- Implement Generative AI and LLM-based applications using RAG pipelines, document intelligence, and model documentation automation. Experience with agentic frameworks like Autogen, LangChain, or similar would be helpful.

- Experience of development and deployment of models in cloud-based platforms such as Azure, AWS, GCP etc.

- Design explainable AI solutions by incorporating techniques like SHAP, LIME, and feature attribution methods to enhance transparency in high-stakes modeling environments.

- Partner with cross-functional teams, including business stakeholders, technology teams, and model governance, to ensure model alignment with business objectives and regulatory expectations.

- Contribute to innovation initiatives and support proposal development, thought leadership, and solution architecture in the AI/ML space.

Required Skills & Experience

- 26 years of total experience, with minimum 2 years in AI/ML or GenAI model development or validation.

- Strong understanding of credit risk modeling frameworks, scorecard development, and risk metrics (e.g., RWA, Expected Loss, Economic Capital).

- Proficient in Python and SQL, with hands-on experience using ML libraries such as scikit-learn, Tensorflow, Pytorch and transformer-based LLM packages

- Familiarity with regulatory standards such as CECL, IFRS 9, CCAR/DFAST, Basel II/III, SR 11-7, and model governance best practices.

- Exposure to cloud environments (Azure preferred), version control (Git), and workflow automation tools.

- Experience with credit bureau data, vendor models (e.g., FICO, Moodys, S&P), and financial benchmarking is a plus.

- Ability to clearly communicate complex technical content to non-technical stakeholders through reports, dashboards, and presentations.

Education & Certifications

- Masters degree or higher in Statistics, Mathematics, Economics, Data Science, Engineering, or Finance.

- Professional certifications such as FRM, CFA, CQF, or in product management equivalent are preferred.

- Contributions to opensource AI / ML projects and competitions is preferred