Senior Quant/AI Developer, Global Markets

Overview

In this role you will develop quantitative models and AI-powered analytics for Global Markets, collaborating with Trading, Structuring and Sales to move ideas from concept to production in UBS’s ACQA platform. You will shape next-generation AI systems and cultivate cross-region partnerships, delivering production-grade solutions for front-office problems. The work combines deep quantitative methods with practical deployment in a fast-paced, collaborative environment. You will drive impact by building robust models, tooling and workflows that support risk-aware decision making.

Pay / Benefits

• career comeback program
• flexible working options
• inclusive culture
• equal opportunity employer

Responsibilities

• Design, develop and implement quantitative models and analytics for Global Markets
• Architect and deploy AI-powered systems from idea to production in collaboration with Trading, Structuring and Sales
• Maintain strong cross-functional relationships with Trading, Structuring, Sales, Quant, IT and Risk
• Develop models, applications and workflows on UBS’s ACQA platform
• Write clean, maintainable code and communicate ideas effectively across regions

Key requirements

• Proficient in Python with track record of delivering production changes to large complex systems
• Front office quant experience with proven production delivery
• Strong communication skills for global stakeholder engagement
• Experience with agentic design (harnesses) and MCP servers and related AI/ML libraries
• Analytical, problem-solving and architectural design skills suited to a front-office environment
• Academic background in Quantitative Finance, Mathematics, Physics, Engineering, Computer Science or related STEM field
• Strong data fundamentals with Python implementations (numpy, polars, scipy)
• Solid knowledge of AI/ML techniques with production experience
• Curiosity about applying AI to improve workflows with sound judgment on outputs and risk standards

• Curiosity and intellectual rigor
• Clear communication and relationship-building across regions
• Strong collaboration and teamwork
• Python production development
• AI/ML techniques and libraries
• numpy

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