Associate Consultant, Model Validation - AI/ML
- Bangalore, Karnataka
- Permanent
- Full-time
Responsible for performing a variety of moderately complex risk analytics with focus on Treasury/ALM and AI/ML models. Resolves moderately complex issues in advanced data
modeling and measuring risk. Provide effective challenge to the models by evaluating model related risks including input data, model assumptions and limitations, conceptual soundness,
methodology, outcomes analysis, benchmarking, monitoring, and model implementation. This role requires a combination of strong quantitative skills and AI/ML technical knowledge.Major Duties
- Validation of moderately complex analytical models used in Treasury, Asset and Liability Management (ALM) and Asset Management
- Validation of Artificial Intelligence (AI), Machine Learning (ML) and Generative AI (GenAI) models
o Evaluate Gen AI model risk, including hallucination, prompt injection, data leakage, reproducibility, and alignment with Responsible AI principles.
o Assess model robustness, interpretability, fairness, and bias through quantitative and qualitative techniques.
- Ensures model development, monitoring, and validation approaches meet regulatory expectations and internal risk management needs.
- Provides analytical or risk measurement support to help meet both internal corporate and regulatory requirements.
- Develop in-depth knowledge of business unit / function and complex modeling techniques used.
- Clearly communicate the complex issues/findings of the model validation outcomes to stake holders.
- Keep abreast with latest regulatory requirements around model risk management.
- Assesses validation requirements and actively provides solutions to enhance the model validation framework.
- As part of centralized Model Validation team within the bank, expected to work on varied areas of risk management.
- Good understanding of Balance sheet, valuation methodologies of fixed income and FX derivatives instruments
- Strong knowledge of AI/ML techniques including classification and clustering, gradient boosting, neural networks, NLP models, and foundational models like GPT, BERT, etc.
- Experience in validating machine learning models for performance, fairness, explainability, and compliance; Familiarity with GenAI risks and controls: hallucination detection, retrieval-augments-generation (RAG), prompt engineering, etc.
- Excellent oral and written communication skills
- Knowledge of risk measurement required to support function.
- Strong analytical and problem-solving skills
- Advanced degree in quantitative discipline (Finance, Math, Statistics, and Economics) or Advanced degree in Computer Science with focus on AI/ML or equivalent career experience preferred.
- A relevant work experience of 4 to 6 years is required.
- Strong Preference for candidates with certifications in AI/ML or CFA/FRM/CQF
- Proficiency in Python and libraries, and Cloud platforms (Azure, AWS)
- 4 to 6 years of relevant experience