Graduate Quant Analyst null

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. We are keen to hear from students with a PhD or Master's degree for this exciting opportunity.

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.

We value creativity and are aggressive to capitalise on opportunities. We take proven strategies to the next level by integrating them across diverse alphas and time horizons using cutting-edge execution technology.

The role:

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 you'll need:

• 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