Thematic Risk Analytics Lead Analyst – Vice President

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. ------------------------------------------------------ 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 Constructive Debate, Escalation Management, Financial Analysis, Issue Management, Management Reporting, Policy and Procedure, Policy and Regulation, Risk Controls and Monitors, Risk Identification and Assessment. ------------------------------------------------------ Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.

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