Squarepoint Capital · London, New York, Singapore, Boston, Paris, Zug, Geneva, Hong Kong, Bangalore · posted 10/28/2026

Please only apply to the one job you feel best fits your skillset and experience. If our team feels you are better suited for another role, we will reach out about the alternate opportunity. Position Overview: - Research statistical techniques such as time-series methods, machine learning and NLP to extract value from data - Analyze large data sets using advanced statistical and ML methods to identify trading opportunities - Help to develop statistical and ML based tools and techniques to solve complex data related problems throughout the firm. Typical Day: - Primary focus throughout the day is on researching new statistical and ML techniques and exploring datasets - Discuss and present research results with other researchers - Deploy and monitor models used to generate trading signals. Required Qualifications: - Quantitative background - includes advanced degrees in computer science, machine learning / NLP, statistics, signal processing, optimization, mathematics and related STEM subjects (masters or higher) - Demonstrated ability for doing high quality and rigorous research, along with communicating results to stakeholders. - Programming proficiency with at least one major programming or scripting language (e.g. python, kdb-q, ) - Strong communication skills and ability to work well with colleagues across multiple regions - Ability to work well in collaborative and high pace settings, and drive projects to completion in accelerated timelines. The minimum base salary for this role is $150,000 if located in New York. This expectation is based on available information at the time of posting. This role may be eligible for discretionary bonuses, which could constitute a significant portion of total compensation. This role may also be eligible for benefits, such as health, dental, and other wellness plans, as well as 401(k) contributions. Successful candidates’ compensation and benefits will be determined in consideration of various factors.

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