Key responsibilities

Are you passionate about using AI to transform the Investment Bank? Do you want to turn strategic opportunities into secure, scalable solutions with measurable business impact?

We're looking for a Data Scientist to:

• partner with stakeholders to identify high-value opportunities and deliver measurable business outcomes such as revenue enablement, risk reduction and productivity
• design, build and deploy production-grade AI solutions across the Investment Bank
• create reusable products using LLMs, agentic systems, machine learning and rules-based analytics
• drive delivery from discovery and prototyping through integration, deployment and adoption
• develop reusable patterns for APIs, system integration, orchestration and observability
• ensure solutions are secure, reliable and maintainable through effective controls, monitoring, testing and documentation
• apply experimentation, quantitative analysis and model evaluation to guide design decisions and demonstrate impact

Your Career Comeback

We are open to applications from career returners. Find out more about our program on ubs.com/careercomeback.

The team

You'll join the IB AI Delivery Hub, with team members based in London and Zurich. The team works with strategic partners across Business, Quant, Risk and Technology to address high-impact challenges and deliver AI capabilities that scale across the Investment Bank.

We combine applied AI expertise, engineering discipline and quantitative judgement with a collaborative, cross-functional approach.

Your skills and experience

• relevant experience in data science, machine learning, applied AI or software engineering, including hands-on experience developing and deploying production LLM-based or agentic AI solutions
• applied AI expertise in natural language processing (NLP), retrieval-augmented generation (RAG) and semantic search
• experience designing AI solutions with effective guardrails, evaluation, monitoring and governance
• advanced Python and software engineering skills, including testing, CI/CD and cloud services
• data engineering experience integrating structured and unstructured data across databases, APIs and enterprise data environments
• quantitative modelling and analytical skills, including statistical analysis and time-series methods
• effective communication and stakeholder-management skills across business and technology functions
• Master's degree or PhD in Computer Science, Engineering, Mathematics, Physics, Quantitative Finance or a related field, or equivalent practical experience
• experience in financial markets, pricing, risk or analytics is an advantage

About us

UBS is a leading and truly global wealth manager and the leading universal bank in Switzerland. We also provide diversified asset management solutions and focused investment banking capabilities. Headquartered in Zurich, Switzerland, UBS is present in more than 50 markets around the globe.
We know that great work is never done alone. That's why we place collaboration at the heart of everything we do. Because together, we're more than ourselves. Want to find out more? Visit ubs.com/careers.

Join us

At UBS, we know that it's our people, with their diverse skills, experiences and backgrounds, who drive our ongoing success. We're dedicated to our craft and passionate about putting our people first, with new challenges, a supportive team, opportunities to grow and flexible working options when possible. Our inclusive culture brings out the best in our employees, wherever they are on their career journey. And we use artificial intelligence (AI) to work smarter and more efficiently. We also recognize that great work is never done alone. That's why collaboration is at the heart of everything we do. Because together, we're more than ourselves.
We're committed to disability inclusion and if you need reasonable accommodation/adjustments throughout our recruitment process, you can always contact us.

Disclaimer / Policy statements

UBS is an Equal Opportunity Employer. We respect and seek to empower each individual and support the diverse cultures, perspectives, skills and experiences within our workforce.