QIS Quantitative Analyst

Overview

As part of UBS’s QIS Quants team, you will help design, build, and deploy quantitative models and analytics for systematic investment strategies. You’ll work with trading, structuring, and IT to prototype new strategies and scale analytics across a cloud-based platform. The role focuses on model development, lifecycle analytics, and collaboration with stakeholders to ensure robust, transparent QIS outputs. This is an opportunity to learn from experienced quants while contributing to risk management and production-grade solutions.

Pay / Benefits

• career comeback program /careercomeback
• flexible working options
• opportunities to learn from experienced practitioners
• global collaboration
• supportive team culture

Responsibilities

• Support design, development, and implementation of quantitative models and analytics for QIS spanning strategy research, pricing, risk, and lifecycle management
• Contribute to modelling and prototyping of new QIS strategies with senior quants and cross-functional partners (Trading, Structuring, Sales)
• Develop robust quantitative tools and workflows to help QIS Trading manage, analyse, and hedge risk
• Assist in transforming the QIS calculation stack toward a strategic, cloud-based architecture with IT and platform teams
• Support internal and external stakeholders (clients, third-party calculation agents, internal platform teams) ensuring robustness, transparency, and scalability of QIS analytics
• Build effective working relationships with Trading, Structuring, Sales, Quant, IT, and Risk partners in London and across regions

Key requirements

• 0–3 years of relevant experience in QIS, systematic trading, quantitative research, structuring, or front-office/quant role within Global Markets
• Proficiency in Python for developing quantitative models, analytics, and applications
• Solid grounding in financial mathematics, time series analysis, and quantitative modelling techniques
• Strong analytical and problem-solving skills with ability to learn in a fast-paced front-office environment
• Good communication skills and collaborative mindset
• Academic background in Mathematics, Physics, Engineering, Computer Science, or related STEM discipline

• curiosity about AI to improve workflows
• sound judgment and risk awareness
• team collaboration
• Python proficiency
• financial mathematics
• time series analysis

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