This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
Are you looking for a career move that will put you at the heart of a global financial institution? Then bring your skills in Data Science and AI solutions to build the next generation Enterprise Document Platform. By Joining Citi, you will become part of a global organisation whose mission is to serve as a trusted partner to our clients by responsibly providing financial services that enable growth and economic progress.
Job Responsibility:
Research and build knowledge in the forefront of AI
Build & maintain a roadmap of AI capabilities from inception to production
Guide data science team to perform their work and growth
Work with product and software development teams from requirements to production
Design, develop, test, support and maintain AI development
Requirements:
8+ years of experience in Data Science, including at least 3 years in a leadership role managing projects or teams
Deep expertise in Document Understanding using Generative AI, including tasks such as information extraction, summarization, classification, and Q&A over unstructured text
Proven experience leading the design, development, and deployment of GenAI solutions with LangChain, Python, and modern LLM frameworks
Strong ability to translate business needs into technical requirements, define solution architectures, and build actionable work plans with clear timelines, milestones, and deliverables
Demonstrated experience in tracking execution, managing team tasks, and delivering regular progress reports and insights to leadership and stakeholders
Familiarity with the Model Risk Management (MRM) lifecycle, including model documentation, testing, validation, and alignment with governance and compliance frameworks
Proficiency in Python and tools such as LangChain, Pandas, PyTorch/TensorFlow, and FastAPI
Strong understanding of prompt engineering, RAG pipelines, vector databases (e.g., FAISS, Chroma), and LLM evaluation strategies
Familiarity with software engineering best practices, including: REST API design and integration, Git version control, CI/CD pipelines, Cloud environments (e.g., AWS, Azure, GCP) and Docker
Track record of building cross-functional collaboration across engineering, product, and business teams to advance GenAI initiatives
Strong communication, mentorship, and leadership skills with a proactive, hands-on approach to delivery and innovation
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