Quantitative Trader

Old Mission is a global proprietary trading firm that leverages state-of-the-art technology and research to identify and execute profitable trading strategies across multiple asset classes around the world. Our offices in Chicago, New York, and London are all composed of naturally-curious individuals who thrive in a team environment and constantly strive for improvement.

About the Position

Old Mission Europe is a quantitative proprietary trading firm and is currently recruiting a quant trader to join our London office. Our traders work in teams to seek out and profitably trade mispriced securities. The quant trader job responsibilities will include disciplined decision making, risk management, derivative pricing, and researching new opportunities.

Required Skills

• An undergraduate or an advanced degree in a quantitative field such as computer science, engineering, or one of the hard sciences

• Proficiency with at least one of the following languages: Python, C++, Java, VBA, R, Matlab, or Ruby

• The ability to work and solve problems as part of a team, often in a high-pressure environment

• 1+ years of relevant trading experience

• Proven trustworthiness and performance under the highest ethical standards

• A strong desire for knowledge and to understand how things work

• Superior written and verbal communication skills

Benefits and Perks

• Competitive salary with discretionary annual bonus

• Fully paid private medical, dental, vision with extended coverage and life insurance

• Robust Pension Scheme, income protection, and salary exchange

• Free on-site lunch daily

• Season Ticket Loan Scheme

• Tuition Reimbursement Program

Old Mission is not accepting unsolicited resumes from any staffing/search firms. All resumes submitted by staffing/search firms to any employee at Old Mission via-email, the Internet or directly without a valid signed search agreement will be deemed the sole property of Old Mission, and no fee will be paid in the event the candidate is hired by Old Mission.