10 weeks Location:
London (on-site)
How to Apply: Please submit your application online on our Careers page. We encourage candidates to express their interests and motivations for their chosen area. Application deadline: 31st January 2025. About the Quantitative Analytics Group (“QAG”) Team: QAG is responsible for developing and maintaining Caxton’s internal analytics platform. The analytics are used internally by portfolio managers and researchers and provide essential data for risk managers and product control. They encompass core derivative pricing and risk analytics as well as trade finding and data-based research tools. The team has a presence in both London and New York and works closely with Caxton’s Quant Development team. The team is currently focused predominantly on interest rates but supports all asset classes as required by the firm. Responsibilities: Assist in the development of Caxton’s internal analytics platform by developing a set of historical curated curve and vol surface data using Caxton's proprietary analytics modelling framework. Engage in other ad-hoc projects related to quantitative finance and data analysis as required by the team. Minimum Requirements: Full availability for the full 10-week duration of the internship from
23 June 2025 – 29 August 2025 . Full-time undergraduate degree in a quantitative subject or a related STEM field and be in their penultimate year, graduating in 2026. Demonstrated keen interest in the financial markets and technology, and the aspiration to work in the financial services industry. Proficiency in written, interpersonal and communication skills to effectively engage with diverse teams and stakeholders. Solid organisational skills, ability to multi-task, and thrive in meeting deadlines within a dynamic, fast-paced environment. Solid programming skills in Python. Strong attention to detail. A curious mindset and a willingness to challenge the status quo. Displays and operates at the highest degree of ethics and integrity. Must be eligible to work in the UK.
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