Description
We are seeking a Quantitative Analytics Associate for our Off Cycle Internship 2027 in Singapore.
As a Quantitative Analytics Associate, you will bring quantitative and analytical expertise to bear across the full spectrum of our Markets and Risk businesses. Our Early Careers colleagues are expected to play an important role in the design and development of risk management and trading strategies, through the use of quantitative analysis, mathematical modelling, and technology, with the aim of optimising trading processes, development practices, systems and infrastructure as well as identifying growth and investment opportunities.
Accountabilities
- Develop and implement quantitative models and strategies to enhance decision-making, pricing, and risk management.
- Design and maintain high-performance trading platforms and risk systems, integrating new features to improve reliability and user experience.
- Conduct research and data analysis to uncover market trends and drive innovation through advanced methodologies and technologies.
- Collaborate with traders, sales teams, and stakeholders in Risk and Finance to deliver customized solutions and translate business needs into scalable tech tools.
- Work cross-functionally with compliance, IT, and strategy teams to resolve system issues and continuously improve trading infrastructure.
The team that delivers world-class solutions
Our Quantitative Analytics team is a global organisation of highly specialised modellers and developers responsible for researching, innovating, developing, testing, implementing, and supporting all quantitative models used for valuation and risk management across all asset classes.
The chance to make a real impact
As an intern in the Quantitative Analytics team, you’ll gain valuable exposure to real-world problems in our dynamic and invigorating environment. During your internship, you will have the chance to work on cutting-edge quantitative and technology problems, which include:
- Apply quantitative techniques to solve real-world business problems
- Research, develop and implement new models and solutions
- Improve our computing or data infrastructure.
A place where you can thrive
At Barclays, you’ll be surrounded by experts in the industry, who will help you achieve your goals and ambitions. Our collaborative, supportive environment gives you the chance to build solid relationships with senior leaders and peers alike. During the programme, you’ll also benefit from in-depth, comprehensive training.
Who we're looking for
To be considered for this programme, you must be a postgraduate student with an anticipated graduation date between December 2027 – June 2028. You should be working towards a postgraduate degree in a technical discipline such as Physics, Mathematics, Operations Research, Quantitative Finance, Economics, Statistics, Stochastic Calculus, Computer Science, or other STEM subjects, with strong programming skills, particularly Python, C++, or Java.