Summary Responsible for performing a variety of moderately complex risk analytics with focus on 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 Artificial Intelligence (AI), Machine Learning (ML) and Generative AI (GenAI) models - Independently validate AI/ML and GenAI models across supervised, unsupervised, reinforcement learning and foundation model categories. - Evaluate Gen AI model risk, including hallucination, prompt injection, data leakage, reproducibility, and alignment with Responsible AI principles. - Assess model robustness, interpretability, fairness, and bias through quantitative and qualitative techniques. - Also responsible for validating complex statistical and/or algorithmic models used across bank in areas such as, Technology/Risk/Regulatory/Capital/Treasury/InterestRate/EconomicResearch/Fraud/Complian e models etc. - Ensures model development, monitoring, and validation approaches meet regulatory expectations as needed 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. Knowledge/Skills - Experience with Machine Learning models (supervised/unsupervised learning, neural networks, classification, clustering, hyperparameter tuning, etc.) desired. - 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. - Good to have some understanding of models used in stress testing, CCAR, CECL, BASEL regulations etc. - Excellent oral and written communication skills. - Knowledge of risk measurement required to support function. - Strong analytical and problem-solving skills. Experience Required - 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 3 to 6 years is required. - Programming experience in Python required, experience in SAS and R desired. - Mastery of analytical tools, such as, Excel as well as Word and PowerPoint is required. - Strong Preference for candidates with certifications in AI/ML or CFA/FRM/CQF - Familiarity with cloud and big data technologies is desired.

Bangalore

Northern Trust - Associate Consultant - Model Validation - Artificial Intelligence/Machine Learning 

Job Description for Northern Trust - Associate Consultant - Model Validation - Artificial Intelligence/Machine Learning  in Northern Operating Services, Pvt Ltd in  Bangalore for (3-6) years of experience. Apply Now!