Data Analytics & AI lead

Key Responsibilities

Strategic Leadership & Vision

• Define and own the multi-year data analytics and AI roadmap for Compliance, aligned with the firm's enterprise data strategy and regulatory commitments.
• Identify and prioritise high-impact use cases for Data Analytics ,AI/ML across credit risk, market risk, operational risk, financial crime, and compliance surveillanc e.
• Serve as the senior subject-matter expert on Data Analytics , AI/ML applications in Compliance management, advising the Barclays Compliance functions on emerging capabilities, risks, and investment priorities.
• Champion a culture of data-driven decision-making across Compliance, driving adoption of advanced analytics among compliance professionals.

Advanced Analytics & AI Delivery

• Lead the design, development, and deployment of machine learning models, NLP solutions, and generative AI applications for risk detection, early warning systems, regulatory reporting, and compliance monitoring.
• Deliver predictive analytics capabilities including, anomaly detection for financial crime, stress testing automation, and real-time surveillance dashboards.
• Architect end-to-end ML pipelines from data ingestion and feature engineering through model training, validation, deployment, and monitoring.
• Drive the adoption of large language models (LLMs) and generative AI for regulatory document analysis, policy gap detection, and automated compliance assessments.

Model Risk & AI Governance

• Establish and enforce robust AI governance frameworks including model risk management, explainability standards, bias detection and mitigation, and responsible AI practices.
• Partner with Model Risk Management (MRM) to ensure all analytics models meet internal validation standards and regulatory expectations (e.g., SS1/23, SR 11-7, TRIM) .
• Maintain comprehensive model inventories, documentation, and performance monitoring dashboards.
• Lead regulatory exam preparedness for AI/ML-related enquiries from the PRA, FCA, and other supervisory bodies.

Data Strategy & Infrastructure

• Collaborate with Chief Data Office, Data Engineering, and Cloud Platform teams to ensure Compliance has access to high-quality, governed, and timely data.
• Define data quality requirements and risk data aggregation standards in alignment with BCBS 239 principles.
• Drive migration of legacy analytics to cloud-native platforms (AWS/Azure/GCP), ensuring scalability, security, and cost efficiency.
• Oversee the development and maintenance of enterprise BI dashboards and reporting solutions using tools such as Power BI, Tableau, and QlikSense.

Stakeholder Engagement & Communication

• Build strong partnerships with senior stakeholders across Compliance, Technology, and Front Office to align analytics priorities with business needs.