Data Scientist – Applied AI & Machine Learning

Your role

Are you interested in helping to design, develop, and deliver AI and machine learning solutions within UBS Global Wealth Management?

Are you experienced in applying advanced ML and GenAI techniques to real-world business challenges, working closely with product, engineering, and business teams to turn strategic priorities into measurable outcomes? Do you want to contribute to the creation of reusable AI components, experimentation frameworks, and intelligent tools that support clients, advisors, and internal operations globally?

We are looking for a Data Scientist to:

• develop, test, and deploy GenAI, agentic, and ML models that address concrete business use cases

• work with cross-functional partners (product, data, and engineering) to design and integrate scalable AI capabilities into existing systems

• build and maintain pipelines for data preparation, experimentation, evaluation, and model monitoring

• contribute to prompt engineering, retrieval-augmented generation (RAG), and other modern NLP and LLM-based applications

• support the development of internal tools and reusable modules (e.g., reasoning agents, evaluation frameworks, feedback loops)

• apply best practices in MLOps, model validation, and responsible AI to ensure quality, transparency, and compliance

Job Type

Full Time

Job Reference #

337055BR

City

Singapore

Your team

This is an opportunity to work at the forefront of UBS’s AI transformation—building meaningful, scalable applications that shape the future of wealth management. You’ll be part of a diverse, forward-thinking team where your ideas can directly influence products used across the globe.

Your expertise

• Master’s or PhD in Computer Science, Machine Learning, Data Science, or related field

• at least 5 years of experience applying ML/AI methods in enterprise or research environments and proven experience with GenAI or NLP applications (LLM fine-tuning, RAG, LangChain, or similar)

• strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow, Scikit-learn, Hugging Face)

• familiarity with MLOps tools (CI/CD, model registry, vector databases, containerization)

• ability to translate business needs into analytical or ML solutions with tangible impact

• strong communication and collaboration skills across technical and business teams

• working knowledge of data privacy, compliance, or governance considerations in regulated industries

• experience integrating AI models with production systems or APIs is an asset

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.