At a Glance
- Tasks: Transform AI opportunities into impactful solutions in a dynamic investment banking environment.
- Company: Join UBS, a leading global investment bank with a focus on innovation.
- Benefits: Enjoy flexible working options, an inclusive culture, and growth opportunities.
- Other info: Be part of a collaborative team driving real business outcomes.
- Why this job: Shape the future of AI in finance while collaborating with a global team.
- Qualifications: Experience in AI/ML, strong Python skills, and a relevant degree or equivalent experience.
The predicted salary is between 63000 - 77000 £ per year.
As a Data Scientist in UBS's Investment Bank AI Delivery Hub, you will translate strategic AI opportunities into secure, scalable solutions with measurable business impact. You will partner with cross-functional stakeholders to drive revenue enablement, risk reduction, and productivity gains, while delivering reusable AI products using LLMs, RAG, and rules-based analytics. You’ll guide projects through discovery to deployment, ensuring secure, testable, and maintainable outcomes. This role offers the chance to shape AI capabilities at scale within a collaborative, global team.
Pay / Benefits
- Flexible working options when possible
- Inclusive culture
- Disability inclusion and accommodation in recruitment
- Opportunities to grow and develop
- Collaborative, global team
Responsibilities
- Partner with stakeholders to identify high-value opportunities linked to business outcomes
- Build and deploy AI solutions across the Investment Bank
- Develop reusable AI components using LLMs, agentic systems, ML, and rules-based analytics
- Contribute across the delivery lifecycle from discovery to adoption
- Integrate solutions with APIs, enterprise systems, and data platforms
- Ensure security, reliability, and maintainability through testing, monitoring, and documentation
- Use experimentation and quantitative analysis to inform design decisions and demonstrate impact
Key requirements
- Hands-on experience building/implementing AI or ML solutions in professional, academic, or internship settings
- Knowledge of NLP, RAG, semantic search, and large language models
- Understanding of model evaluation, testing, monitoring, and responsible AI practices
- Strong Python skills; productionising AI/ML with versioning, automated testing, CI/CD, deployment, monitoring
- Experience with structured and unstructured data across databases, APIs, and data environments
- Analytical and problem-solving skills with statistical analysis and data exploration
- Effective communication and cross-functional collaboration
- Bachelor or Master in CS, Engineering, Math, Physics, Quantitative Finance, Data Science, or related field, or equivalent experience
- Experience in financial markets, pricing, risk, or analytics is advantageous
Data Scientist, Investment Bank employer: UBS
UBS is an exceptional employer, offering a dynamic work environment in London where collaboration and innovation thrive. As a CCP Risk Manager, you'll benefit from a culture that prioritises employee growth, providing opportunities to tackle complex challenges while utilising cutting-edge AI technologies. With a commitment to inclusivity and flexible working options, UBS ensures that every team member can contribute meaningfully to our collective success.
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We think this is how you could land Data Scientist, Investment Bank
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We think you need these skills to ace Data Scientist, Investment Bank
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at UBS. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at UBS
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at UBS!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
