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.
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- 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:
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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.
For complementary skills, please see above and/or contact the recruiter. ------------------------------------------------------
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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