Solution Architect

Job Location:

Gurgaon/ Mumbai/ Bangalore/ Chennai/ Pune/ Other Cities

Senior Model Validation Consultant for Artificial Intelligence and Machine Learning Models

The role involves working with senior leaders to design and establish model risk management programs at leading financial institutions for artificial intelligence and machine learning models used in credit /market/ liquidity/ valuation / other areas. It requires ability to map, align and combine technology neutral model risk management directives such as SR 11-7, SS 1/23, E-23, APS 117, CBUAE MMS 2022 to AI/ ML specific frameworks such as NIST AI, EU AI Act, ISO 42000, MAS guidelines etc. It also requires experience and ability to provide transformative benefits in terms of reusable frameworks, assets and accelerators for insights and productivity gains as an essential deliverable of the model validation and review assignments.

Typical responsibilities for the senior quantitative analyst include:

Lead development of validation frameworks for supervised/ unsupervised/ reinforcement learning AI/ ML models across credit risk/ market risk/ liquidity risk/ valuation and other use cases where validation frameworks include:

• Model methodology specific testing approaches
• Evaluation of model fairness, explainability, and interpretability using model specific and model agnostic metrics, using FEAT framework etc.
• Compliance approach to EU AI Act, NIST AI, ISO 42000 Framework, etc
• Risk assessment considering redteaming, performance efficiency,
• Collaborate with engineering team to build and/or adapt open-source libraries and tools for efficiency gains in model validation, testing and documentation assignments.
• Manage and execute model validation assignments with seed / transition teams with an ultimate objective of building and handing over delivery to ongoing delivery teams at the account level. Management of model validation assignments include:
• Drafting a validation work plan and testing framework as per industry best practices and applicable regulatory guidelines
• Conducting qualitative and quantitative reviews of the models including XAI analysis, hyperparameter tuning, data /conceptual drift, overfitting and stress testing of overfitting remedial measures
• Carrying out discussions with model owners to review model documentation in terms of mathematical and technical fundamentals
• Developing an approach for benchmarking the models
• Conducting model implementation testing
• Summarizing findings based on test results and carrying out discussions with model owners to arrive at a remediation plan
• Drafting validation reports with clearly defined assessments for model materiality, tiering, model assumptions and limitations, restrictions on model usage;

Professional experience and academic qualifications

• Undergraduate/ Post Graduate Degree in Computer Science, Mathematics, Statistics, Data Science
• 3+ years of experience specifically in the area of model validation of AI/ML models
• Hands on programming experience in Python for AI/ML models, experience with ML frameworks ( e.g. scikit-learn, XGBoost, tensorflow, Pytorch)
• Understanding of MLOps and model lifecycle management
• Hands on programming experience in Python
• Strong communication skills including business writing is a must