Maven is a proprietary trading and market making organisation formed in 2011. We employ the most talented traders, developers and engineers in the market, executing a diverse range of strategies across global equities and derivatives. We are the most active participant in many of the products we trade, contributing significant liquidity to markets around the world.
Maven’s Systematic Alpha team deploys methodically researched strategies across futures, options and equities, utilising some of the most advanced technology available. Our approach to trading is scientific and process driven, with a strong emphasis on a flexible research environment, providing us efficient means to develop, test, and deploy new ideas. We empower our team members and maximise their ability to succeed by offering an environment that is open, collaborative and supportive.
As a Quant Analyst, you will complete intensive training, and work collaboratively with traders and researchers from various scientific fields and prestigious academic institutions to tackle problems in the computational, data processing, signal generation, and signal combination spaces. We will teach you the skills to develop expertise in doing quantitative research and development across a variety of financial domains and time-horizons including: options, futures, and equities.You will apply your academic research abilities and learn how to perform research on real-world data of varied volume and sampling frequency across a variety of domains.
Quant Analysts will achieve this through a combination of classroom sessions and real world projects with the opportunity to iterate on ideas quickly and see the impact of their work in production.
What we're looking for:
PhD or Master’s degree in Science, technology, engineering, and mathematics Strong mathematical skills including: statistics, probability, AI/Machine Learning, mathematical programming, optimisation Strong coding skills: Python and familiarity with a variety of statistical packages Enthusiasm to learn about new quantitative and computational methods for solving complex mathematical problems Exposure to real-world data exploration, dimension reduction, and feature engineering Ability to work independently, present new ideas, approaches, and take direction from senior staff
Why you should apply:
Direct exposure and training from industry leaders A flexible research environment whereby technology is key to our success Freedom to pursue new innovative solutions and implement them into production A highly collaborative environment giving you the exposure to learn from other areas of the business Great friendly, informal and highly rewarding culture Informal dress code, loads of social events, etc
The deadline for applications is 17 December 2020 « Return to the search results