Job Description:

Introduction 

An individual in Enterprise Risk Management plays a critical role in managing the bank's diverse risks to ensure financial stability and sustained growth. This involves the identification and management of enterprise-level and cross-cutting risks, designing and executing stress tests, managing climate risk, and protecting against reputational risk. This integral role within the bank ensures operations are within a defined risk appetite and contribute to the overall objectives of the bank. 

This role is a unique and exciting opportunity to build the future of thematic risk using cutting-edge data science and AI. 

Responsibilities 

• Lead the design, development, and strategic deployment of advanced AI and machine learning models to identify, analyze, and monitor emerging thematic risks across global markets. 

• Drive the conception and implementation of sophisticated Agentic AI systems for autonomous and proactive risk detection, analysis, and alerting. 

• Architect and oversee the management of large-scale Knowledge Graphs to map and understand complex, interconnected risk ecosystems. 

• Leverage Retrieval-Augmented Generation (RAG) techniques to extract and synthesize actionable intelligence from vast unstructured and structured datasets. 

• Champion the development of proof-of-concepts and rapidly prototype new AI-driven risk management tools and platforms, guiding their evolution to production. 

• Independently design and execute analysis of large-scale data populations aggregated from target platforms, processes, and product lines, consisting of structured and unstructured data. 

• Strategically identify, quantify, and effectively communicate emerging risk from aggregated data not identified by the enterprise in isolated processes to drive proactive risk mitigation. 

• Lead collaboration efforts with risk managers, quantitative analysts, and business stakeholders to integrate AI solutions into strategic decision-making processes. 

• Lead all aspects of risk and control analysis and validation in line with established standards, providing comprehensive risk mitigation recommendations and strategic guidance. 

• Drive and oversee remediation efforts related to audit, compliance, and regulatory findings, establish the quarterly audit process, and manage procedural implementation and change management to ensure sound governance and controls. 

• Initiate and lead efforts to enhance and automate control processes, and oversee the monitoring of control exceptions and breaches. 

• Establish and actively promote strong governance, controls, and a culture of responsible finance, leading the implementation and oversight of the Control Framework. 

Recommended Qualifications 

Core AI Concepts: 

• Generative AI (GenAI): Deep understanding and practical application of generative models. 

• Agentic AI: Experience in building and deploying autonomous AI agents. 

• Retrieval-Augmented Generation (RAG): Expertise in leveraging RAG for enhanced information synthesis. 

• Knowledge Graphs: Proven ability to construct and utilize knowledge graphs for complex data representation. 

Technical Skills and Qualifications: 

• Programming & Frameworks: 

• Proficiency in: Python 

• Good to Have Libraries: LangChain, LangSmith, LangGraph, Streamlit, PyTorch, FastAPI. 

• Database Technologies: 

• Good to Have: Graph Databases (Neo4j), Vector Databases (PGVector, Milvus, Pinecone) 

• Relational Databases: PostgreSQL, SQL 

• Unstructured Data Expertise: Ability to extract, clean, transform, and analyze unstructured data from diverse sources such as customer complaints, issues, etc. 

• Natural Language Processing & Machine Learning Skills: Expertise in text preprocessing (tokenization, stemming, lemmatization), named entity recognition, sentiment analysis, and applying Machine Learning algorithms like classification, clustering, and topic modeling. 

• Insights & Reporting: Experience converting processed unstructured data into actionable insights using visualizations, dashboards, and automated reporting tools. 

• Exposure to Google Cloud Platform (GCP) or Amazon Web Services (AWS) is required. 

Experience and Competencies: 

• 10+ years of experience in Data Science, with banking and finance experience preferred but not mandatory. 

• Demonstrated leadership in establishing strong governance and controls, and fostering a culture of responsible finance, good governance, and ethics. 

• Proven track record of designing and leading complex projects that significantly enhance processes, showcasing exceptional creativity in problem-solving. 

• Maintains expert knowledge of evolving requirements and their impacts, responsible for significant business results and technical strategy. 

• Strong leadership skills to manage governance and foster a culture of responsible finance and ethics. 

• Exceptional communication and stakeholder management skills to effectively liaise with various stakeholders across the business. 

Education 

• Bachelor's/University degree, Master's degree preferred.