Data Scientist, Investment Bank

Overview

In this role you will drive AI-driven transformations within UBS Investment Bank. You will partner with cross-functional stakeholders to identify high-value opportunities and deliver scalable AI solutions. You’ll build reusable AI components using LLMs, RAG, and other ML techniques, and guide projects from discovery to deployment. You will ensure secure, reliable, and well-documented solutions while measuring impact through experiments and analytics. This is a hands-on, collaborative role in the IB AI Delivery Hub that shapes how AI enables revenue, risk reduction, and productivity at scale.

Pay / Benefits

• flexible working options when possible
• inclusive culture
• disability inclusion and accommodation throughout recruitment

Responsibilities

• Partner with stakeholders to identify high-value opportunities and contribute to business outcomes such as revenue enablement, risk reduction, and productivity improvement
• Build and deploy AI solutions across the Investment Bank
• Develop reusable products and components using LLMs, agentic systems, machine learning, and rules-based analytics
• Contribute throughout the delivery lifecycle, from discovery and prototyping through integration, deployment, and adoption
• Integrate solutions with APIs, enterprise systems, and data platforms
• Ensure solutions are secure, reliable, and maintainable through testing, monitoring, controls, and documentation
• Apply experimentation, quantitative analysis, and model evaluation to inform design decisions and demonstrate impact

Key requirements

• Hands-on experience building and implementing AI or machine learning solutions in professional, academic, or internship settings
• Knowledge of NLP, retrieval-augmented generation (RAG), semantic search, and large language models
• Understanding of model evaluation, testing, monitoring, and responsible AI practices
• Solid Python programming skills and productionising AI/ML solutions, including version control, automated testing, CI/CD, deployment, and monitoring
• Experience working with structured and unstructured data across databases, APIs, and other data environments
• Strong analytical and problem-solving skills, including statistical analysis and data exploration
• Effective communication and collaboration with stakeholders across business and technology functions
• A bachelor’s or master’s degree in Computer Science, Engineering, Mathematics, Physics, Quantitative Finance, Data Science, or related field, or equivalent practical experience
• Experience in financial markets, pricing, risk, or analytics is an advantage

• Effective communication
• Collaboration across cross-functional teams
• Problem-solving
• NLP
• Retrieval-Augmented Generation (RAG)
• Semantic search

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