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Experienced/Lateral - Quantitative Researcher

Five Rings
CompanyFive Rings
CategoryScience & Research
LocationLondon
RemoteOn-site (inferred)
EmploymentNot stated
LevelMid
SalaryNot stated by the employer
Posted21 Apr 2025
Last verified11 Aug 2026
SourceThe employer's own careers page (company_site)
Applications are handled by the employer, not by us.Apply on the employer's site →
Description
**About Five Rings** Five Rings is a proprietary trading firm founded with a vision of combining strategy, innovation and technology to succeed in today's global markets. With offices in New York, Boca Raton, London and Amsterdam, Five Rings trades in various domestic and international markets, both established and esoteric. Our team constantly seeks new opportunities, analyzes their risks and rewards, and creates strategies and tools to capitalize on them. We have an open culture and encourage the flow of knowledge and ideas between all areas of the firm. **About the Role** Five Rings gives people as much responsibility as possible, as quickly as it can be earned. - Identify new opportunities in the markets we trade - Construct or enhance market models - Develop analyses and simulations - Implement models in our trading systems - Test models in real time - Collaborate with traders and software developers **About You** - Must possess a Bachelor's degree in computer science, economics, mathematics, physics, statistics, or another qualifying field. - Minimum of two years' work experience involving the development of quantitative trading strategies. - Experience conducting data analysis involving large financial datasets to find signals for mid- to high-frequency trading - Exceptionally mathematically proficient - Possesses a hunger to work on some of the most complex mathematical problems - Risk taker and problem solver - Explores innovative thinking and analytical methodologies - Extremely detail-oriented and thrives in a fast-paced, highly collaborative environment - Eager to continue to learn and grow your skills - Proficiency in statistical languages and/or packages in R, python, or similar. *Applicants are able to apply to multiple positions, but we strongly encourage you to only apply to your top choice.*