Fraud & Aiml Validation

Job Title : Fraud & AIML Validation
Location: Noida

About Barclays
Barclays is a British universal bank. We are diversified by business, by different types of customers and clients, and by geography. Our businesses include consumer banking and payments operations around the world, as well as a top-tier, full service, global corporate and investment bank, all of which are supported by our service company which provides technology, operations and functional services across the Group.

Risk and Control Objective

Take ownership for managing risk and strengthening controls in relation to the work you do

Working Flexibly

Hybrid Working

Structured hybrid role:
Introduction:
1. Provide independent review (IR) for various types of validations and challenge different aspects of material / key models (Data Relevance & Quality, Conceptual Soundness, Model Performance etc.) across different model types: Strategic, Artificial Intelligence/Machine Learning (AI/ML); Random Forest, Gradient Boosted Machines and Deep Neural Networks; Regression, Decision Trees Large Language model (LLM), Natural Language Processing (NLP), etc. to a degree of depth, as required by and detailed in the Bank’s policies, procedures, and standards.
a. Engage with model owner and developers to ensure all supporting material required for validation is received timely, in accordance with the validation schedule.
b. Perform technical analysis, independent tests, benchmarking, build challenger models to support the IVU review and challenge process for all new and existing models, to ensure accuracy of existing risk metrics to the standards required by IVU and to drive continuous improvements in methodologies.
c. Produce high quality MRM validation documentation leveraging the latest procedure, standard and templates.
2. Provide input to/support the governance and reporting processes related to model risk management.

What will you be doing?

1. Key Model Validations
a. Validate Strategic and Artificial Intelligence/Machine Learning (AI/ML) based models across the bank by following Bank’s policies, procedures, and standards.
b. Perform technical analysis, independent tests and/or build alternative benchmarks to new and existing models, in line with the requirements set out in the bank’s policies, procedures, and standards.
2. Governance and Reporting
a. Review regulatory requirements to ensure compliance with different regulatory guidelines e.g., SR 11-7, SS 1/23, PRA, FRB.
b. Support the development and review conformance with appropriate policies including Group Model Risk policy.
3. Stakeholder Management
a. Ensure open, transparent, proactive, and timely interaction with major stakeholders (model owners/ developers) in alignment with Barclays Values and Behaviour principles.
b. Establish and maintain effective working relationship with the key stakeholders across businesses served.
c. Role requires influencing skills and problem-solving abilities to overcome issues inherently arising during the validation process.
4. Additional Engagements
a. Contribute to create presentations based on validation related topics for relevant model governance committees.
b. Contribute to AI/ML related trainings anchored by the incumbent team.
c. Support the model management team in tracking actions and the accuracy of Group Model Database (GMD).

What we’re looking for:
Essential
- Expertise on quantitative techniques used in developing and validating models including Strategic, AI/ML - Large Language model (LLM), Natural Language Processing (NLP), Random Forests, Gradient Boosted Machines, Deep Neural Networks, decision trees and cluster analysis.
- Strong analytical skills with experience developing or validating predictive machine learning models (e.g., Large Random Forests, Gradient Boosted Machines and Deep Neural Networks, Language model (LLM), Natural Language Processing (NLP) etc.) on large data sets in in Hadoop/AWS environments using tools such as Python, Spark and MLLib with high focus on gaps/ issue identification.
- Proven expertise/in depth knowledge of one or more of the following areas of model risk management: Fraud, IFRS9, Basel, Application/Behavioural Risk scorecards, Existing Customer Management etc.
- Good communication and influencing ability to effectively follow through on requirements from stakeholder and strong documentation expertise.
- Hands-on experience in the use of statistical packages such as SAS, R, Python. Expert user of Microsoft Excel, Word, PowerPoint, and other Microsoft Office tools.
- An ability to identify and analyse appropriate external data sources for model development or validation.

Skills that will help you in the role:
Preferred:

- Relevant experience in a modeller/validator role in the financial services industry.
- Certification in Machine Learning

Education
- Masters in Statistics, Mathematics, Economics, Operational Research, Engineering, MBA

Where will you be working?
Noida

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