Thematic Risk Analytics Sr Analyst - Assistant Vice President

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 contribute to building the future of thematic risk using cutting-edge data science and AI. 

Responsibilities 

• Develop and deploy advanced AI and machine learning models to identify, analyze, and monitor emerging thematic risks across global markets, contributing to their design. 

• Implement and contribute to the building of sophisticated Agentic AI systems for autonomous and proactive risk detection, analysis, and alerting. 

• Contribute to the construction and 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. 

• Contribute to the development of proof-of-concepts and rapidly prototype new AI-driven risk management tools and platforms. 

• Execute analysis of large-scale data populations aggregated from target platforms, processes, and product lines, consisting of structured and unstructured data, with guidance on design as needed. 

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

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

Recommended Qualifications 

Core AI Concepts: 

• Generative AI (GenAI): 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: 

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

• Experience in promoting strong governance and controls, and contributing to a culture of responsible finance, good governance, and ethics. 

• Proven ability to contribute to and execute projects that enhance processes, demonstrating problem-solving in complex situations. 

• Maintains knowledge of evolving requirements and their impacts, contributing to business results and technical strategy. 

• Strong communication skills to liaise with various stakeholders across the business. 

Education 

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