Job Description
Responsibilities Independently assess AI/ML/data science model purpose, assumptions, features, data inputs, and logical soundness. Evaluate feature engineering, data quality, and detect issues such as leakage or mis-specified inputs. Evaluate model performance using suitable metrics, diagnostic tests, and validation methodologies. Assess stability, robustness, sensitivity analysis, susceptibility to adversarial attacks and model or concept drift. Apply model explainability methods such as SHAP, LIME and other interpretability techniques. Produce comprehensive, well-reasoned Model Validation Reports. Evaluate AI/ML models, LLMs, retrieval-augmented systems, agentic workflows, and prompt-engineering methods. Ensure validation standards align with Responsible AI principles including fairness, transparency, and robustness. Collaborate with data scientists and model developers across business and functional teams to understand modelling intent, design rationale, and underlying assumptions. ...