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Data Analyst

UBS

London, England, United KingdomOn Site

Original Job Summary

About the Data Analyst Role at UBS

Do you want to apply your expertise in software engineering to propel hypothesis-driven empirical research? As a Data Analyst at UBS, you will join a diverse and globally distributed team to design and implement analytical tools for sell-side equity research.

Your Role

  • Design and implement analytical tools for enterprise statistical computing.
  • Develop a shared ecosystem enabling reproducible, scalable, and collaborative data analysis workflows.
  • Drive development of LLM-powered tools and Agentic AI workflows.
  • Build and maintain applications that facilitate dynamic, real-time collaboration.
  • Provide one-on-one coaching and lead workshops for investment professionals.
  • Collaborate with cross-functional teams to integrate research workflows with enterprise systems.

Your Expertise

  • Proven experience with software development principles applied to empirical research workflows.
  • Strong track record in developing applications using Python and object-oriented programming.
  • Solid foundation in statistical modelling, causal inference, or machine learning.
  • Formal training in empirical methods or equivalent professional experience.
  • Hands-on experience with designing or deploying LLM-based systems is a major plus.

About UBS

UBS is the world’s largest and only truly global wealth manager, with a presence in over 50 countries. Join a team that values diversity, global collaboration, and innovation in sell-side equity research.

Key Skills/Competency

  • Data Analysis
  • Python
  • Statistical Modeling
  • Machine Learning
  • Empirical Research
  • LLM Systems
  • Software Engineering
  • Collaboration
  • Workshops
  • Real-time Data

How to Get Hired at UBS

🎯 Tips for Getting Hired

  • Research UBS culture: Study mission, values, and recent news on Glassdoor.
  • Customize your resume: Tailor experience to data analysis and software projects.
  • Highlight technical skills: Emphasize Python and statistical background.
  • Prepare for interviews: Practice real-world problem solving scenarios.

📝 Interview Preparation Advice

Technical Preparation

Review Python coding challenges.
Practice statistical model exercises.
Test object-oriented programming tasks.
Study LLM system deployment basics.

Behavioral Questions

Describe a team conflict resolution experience.
Explain handling project deadlines under pressure.
Share initiative in cross-team collaboration.
Discuss adapting to new technologies quickly.