Job Description
Citi is a leading global financial institution, and they are seeking a Data Scientist, Generative AI within their Spread Products division. This role involves pioneering AI solutions to enhance trading, risk management, and client solutions in capital markets, focusing on Generative AI techniques and data engineering.
Responsibilities
- Pioneer Generative AI Solutions: Design, develop, and deploy production-grade AI applications leveraging state-of-the-art Generative AI techniques, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and advanced agentic frameworks tailored for capital markets
- Drive Workflow Transformation: Construct innovative AI/data solutions that significantly enhance workflows and operational efficiency across a diverse range of product classes, such as corporate bonds, Mortgage-Backed Securities (MBS), Collateralized Loan Obligations (CLOs), and derivative instruments
- Advance Autonomous Systems: Architect and implement agentic coding systems capable of autonomously generating, testing, and optimizing complex financial models and analytical tools specifically for credit and securitized markets
- Build Intelligent Interfaces: Develop intuitive conversational AI interfaces and intelligent assistants to empower originators, structurers, investors, lenders, and market makers within the Spread Products ecosystem
- Engineer Robust Data Pipelines: Design, construct, and maintain scalable data pipelines to underpin advanced AI/ML workflows, seamlessly integrating vast datasets including real-time market data, comprehensive credit data, securitized product performance analytics, and proprietary research content
- Seamless AI Integration: Develop robust APIs and microservices to effectively embed AI capabilities into Citi's critical capital markets, credit, and securitized product platforms
- Optimize Data Infrastructure: Implement and optimize high-performance data storage and retrieval solutions capable of managing and processing large volumes of complex credit and securitized market data for demanding AI applications
- Champion Data Automation: Contribute to the strategic automation and lifecycle management of data assets across the entire Spread Products business
- Strategic Business Partnership: Actively collaborate with diverse business stakeholders across all product lines and geographies within Spread Products to identify, prioritize, and champion high-impact AI implementation opportunities
- Quant Research Synergy: Partner closely with quantitative researchers to integrate cutting-edge AI techniques into sophisticated credit and securitization pricing, advanced risk models, and optimized portfolio management strategies
- Regulatory Adherence & Governance: Work proactively with compliance, legal, and risk management teams to ensure all AI solutions adhere strictly to regulatory frameworks and governance requirements specific to the capital markets domain
- Continuous Learning & Innovation: Maintain deep expertise in emerging AI technologies, methodologies, and industry trends, continuously evaluating their potential applicability and value to Spread Products' evolving business needs
- Foster AI Community: Actively contribute to and engage with Citi's broader AI/ML community of practice, fostering knowledge sharing, best practices, and collaborative innovation across the firm
Skills
- Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Artificial Intelligence, Quantitative Finance, or a closely related quantitative field
- Exceptional academic grounding in algorithms, data structures, software engineering principles, and computational mathematics
- 1-5 years of progressive professional experience in AI/ML engineering, advanced software development, or data science roles, with a strong preference for backgrounds within financial services or capital markets
- Proven track record of successfully designing, developing, and deploying robust, production-grade AI applications in complex environments
- Direct experience or strong foundational understanding of credit markets, securitized products, or other relevant financial instruments is highly advantageous
- Deep, hands-on experience with state-of-the-art Generative AI techniques, including practical application and fine-tuning of Large Language Models (LLMs) such as GPT, Claude, Llama, or similar architectures
- Demonstrated expertise in designing and implementing Retrieval-Augmented Generation (RAG) systems for enterprise applications
- Practical experience with agentic frameworks and the development of autonomous coding or intelligent decision-making systems
- Comprehensive knowledge of classical and modern machine learning algorithms, statistical modeling, and experimental design
- Solid understanding of financial mathematics, quantitative modeling, and their application within capital markets
- Demonstrated proficiency in Python, including experience with relevant data science libraries (e.g., Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow) and software development best practices (e.g., version control, testing, clean code)
- Advanced SQL skills with experience querying and optimizing performance on large, complex datasets
Benefits
- Medical, dental & vision coverage
- 401(k)
- Life, accident, and disability insurance
- Wellness programs
- Paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays
Company Overview
Company H1B Sponsorship
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