IB Quants – Quantitative Analyst (QIS AI & Automation) (m|f|x) London

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.

Tasks

• Design, develop, and support quantitative analytics, applications, and automation solutions supporting the QIS business.
• Partner directly with QIS business to understand business requirements and rapidly deliver impactful solutions.
• Build AI-enabled applications leveraging Large Language Models (LLMs), Agentic AI architectures, Model Context Protocol (MCP), Retrieval-Augmented Generation (RAG), and machine learning techniques.
• Develop tools supporting QIS strategy management, monitoring, and hedging activities.
• Contribute to the automation and industrialisation of QIS strategy workflows, calculations, controls, and operational processes
• Collaborate closely with peer Quant, Trading, Structuring, Sales, Risk, and Technology teams globally throughout the full development lifecycle.

Profile / Your qualification / Your personality

Must-have skills & experience

• Education & Professional Experience
• 5+ years of experience in a quantitative analyst, quantitative developer, AI engineering, machine learning, systematic trading, or front-office analytics role.
• Bachelor's, Master's, or PhD degree in Mathematics, Physics, Engineering, Computer Science, Statistics, Financial Engineering, or a related quantitative discipline.
• Proven experience delivering production-grade analytics, automation, or AI-enabled solutions.
• Experience working directly with business stakeholders to translate requirements into scalable technical solutions.
• Quantitative Finance & Business Knowledge
• Understanding of quantitative finance, derivatives, systematic investment strategies, risk management, or Front Office trading workflows.
• Strong analytical and problem-solving skills with the ability to develop practical solutions to complex business challenges.
• Strong communication and stakeholder management skills.
• Interest in quantitative investment products and strategy lifecycle management.
• Software Engineering
• Strong Python development skills with experience building production-quality applications.
• Strong understanding of software engineering principles, including data structures, algorithms, software design, API development, testing, and version control.
• Experience developing scalable analytics, automation, or data-driven applications.
• AI & Intelligent Automation
• Experience designing, building, or deploying AI-enabled applications, analytics platforms, or workflow automation solutions.
• Practical experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI architectures, multi-agent systems, or semantic search and knowledge retrieval systems.
• Experience using AI frameworks such as LangGraph, LangChain, Semantic Kernel, AutoGen, CrewAI, Microsoft Copilot Studio, OpenAI Agents SDK, or similar enterprise AI frameworks.
• Experience building or integrating Model Context Protocol (MCP) servers, tools, or workflows that connect AI applications with enterprise systems and business processes.

Nice-to-have skills

• QIS & Front Office Experience
• Experience supporting Quantitative Investment Strategies (QIS), systematic investment products, index businesses, structured solutions, or systematic trading platforms.
• Experience developing trader-facing analytics, pricing, risk management, hedging, or workflow automation solutions.
• Experience within Equity Derivatives, Rates, FX, Electronic Trading, or Multi-Asset businesses.
• Additional Technology Experience
• Proficiency in C++, Java, or C#.
• Experience with KDB+/q, Kafka, Kubernetes, Docker, cloud platforms (Azure, AWS, or GCP), vector databases, or distributed computing technologies.
• Advanced AI & Data Experience
• Experience deploying machine learning models in production environments.
• Experience building agentic workflows, MCP-based integrations, enterprise AI applications, or intelligent automation

  platforms at scale.

Additional Differentiators

• Understanding of quantitative research, index methodologies, systematic strategies, electronic trading, or market microstructure.
• Demonstrated ability to rapidly learn new business domains and deliver high-quality solutions in a fast-paced Front Office environment.

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Location

5 Broadgate, GB-EC2M 2QS London