At a Glance
- Tasks: Design and implement AI solutions for Global Markets, collaborating with diverse teams.
- Company: Join UBS, a leading global financial services firm with a dynamic culture.
- Benefits: Full-time role with competitive salary and opportunities for professional growth.
- Other info: Fast-paced environment with strong emphasis on collaboration and innovation.
- Why this job: Make an impact by solving real-world problems using cutting-edge AI technology.
- Qualifications: Proficient in Python, with experience in quantitative finance and AI/ML techniques.
The predicted salary is between 70000 - 90000 £ per year.
Your role
Are you excited by the prospect of engineering solutions across Global Markets? Do you want to design, build and help deliver production systems across the front‑office? Are you passionate about building and delivering AI solutions?
We’re looking for a Senior Quant/AI Developer to:
- Participate in the design, development, and implementation of quantitative models and analytics across the Global Markets business
- Play a key role in designing and implementing the next generation of AI‑powered systems, partnering closely with Trading, Structuring and Sales from idea generation through to production launch
- Build and maintain strong working relationships with Trading, Structuring, Sales, Quant, IT, and Risk partners in London and across regions
Your team
You’ll be working in our Quantitative Analytics team in London – a fast‑paced, entrepreneurial environment. We build the tools, models, and workflows that drive the Front Office across asset classes, working side‑by‑side with them to architect solutions to real problems. You’ll develop models, applications, and workflows within UBS’s proprietary cloud‑based quantitative analytics platform (ACQA), working closely with Trading, Structuring, Sales, Quant, and IT partners globally. Clean code, curiosity and the ability to build relationships and communicate ideas is crucial to the team delivering across a broad range of problems.
Your expertise
- An ambitious and intellectually curious individual, keen to combine your technical experience with a clear desire to solve practical problems
- Proficient in Python with experience delivering production changes to large complex systems
- Previous experience in a front‑office quant role demonstrating a clear track record of production delivery
- Able to communicate your ideas clearly and build strong relationships globally within the front office
- Previous experience of agentic design (harnesses), MCP servers, and related AI/ML python libraries
- Strong analytical, problem‑solving, and architectural design skills, with an ability to operate effectively in a front‑office environment
- An academic background in Quantitative Finance, Mathematics, Physics, Engineering, Computer Science, or a related STEM discipline
- Strong understanding of data fundamentals and their python implementations (numpy, polars, scipy)
- Strong knowledge of AI/ML techniques with experience delivering related work into production
- You’re curious to explore how AI can improve how we build, deliver, and optimize workflows. You do this with sound judgment – validating outputs and aligning with policies, risk standards, and ethical use.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Quant/AI Developer, Global Markets in London
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We think you need these skills to ace Senior Quant/AI Developer, Global Markets in London
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!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at UBS, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
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.
