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.  

Job Family Group: Risk Management

Job Family: Regulatory Risk

Time Type: Full time

Most Relevant Skills Analytical Thinking, Credible Challenge, Governance, Policy, Procedure, and Regulation, Risk Management Lifecycle, Stakeholder Management.

Other Relevant Skills For complementary skills, please see above and/or contact the recruiter.

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