
Data-driven investment management for superior returns
Squarepoint Capital is a prominent investment management firm headquartered in London, specializing in quantitative trading and investment strategies. With a team of over 300 professionals, Squarepoint leverages advanced technology and data analytics to manage a diverse portfolio for institutional c...
Squarepoint Capital offers competitive salaries, performance-based bonuses, comprehensive health benefits, and a generous PTO policy. Employees also h...
Squarepoint Capital fosters a culture of intellectual rigor and innovation, emphasizing data-driven decision-making and collaboration among its teams....

Squarepoint Capital • Boston, Geneva, Houston, Hong Kong, London, Paris, New York, Montreal, Singapore, Warsaw, Zug
Position Overview:
In the context of our high-frequency trading business, researchers are constantly crunching large datasets in order to decode the inner workings of the market and improve trading models. We're looking for a candidate capable of building, supporting, and extending the functionality of Python-based research tools critical to the success of the business. Candidates should be proficient in manipulating large amounts of data with open-source Python packages (Polars/Pyarrow/Numba) and be familiar with at least one compiled language (Rust/C++/C). Prior experience utilizing distributed computing frameworks (e.g. Slurm/Dask/Spark) is also helpful. The candidate is expected to actively collaborate with other developers and researchers to add or enhance requested features and improve performance.
Required qualifications:
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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