Quantitative Researcher (Full-Time - Master’s/Bachelor’s)

Radix Trading University Job Board•Chicago, IL

About The Position

As a Quantitative Researcher, your focus is on identifying trading opportunities, but you can add even more value with strong quantitative skills and some coding proficiency to accelerate the innovation process and help others leverage your work. By working on a variety of projects with different collaborators over the start of your career, you’ll gain new knowledge and insight into the fundamentals of market dynamics, trading strategies, and our proprietary research platform. We believe in learning through impactful work, so while you learn the intricacies of our industry, you’ll have plenty of opportunities to contribute and directly affect our bottom line within your first few weeks on the team. While interest in trading is key, a background in finance is definitely not. Our team is built mostly from academia — not from other trading firms. We seek mental diversity and add a select group of academics each year from a wide range of disciplines.

Requirements

Highly analytical people (math, physics, computer science, statistics, electrical engineering, etc.)
Persistent Drive to Improve
Creative Problem Solving and Probabilistic Thinking
Ability to learn and implement new concepts quickly
Ability to combine knowledge from different domains to create new ideas
Data-driven and probabilistic approach to testing and implementing new ideas
Team Mindset
Mental Flexibility & Self Awareness
Orientation for Making Money
Research / Quant trading strategy skills to have or develop
Strong intuition and deep thinking with data sets
Demonstrates strong “hacking” ability to quickly get into data to look for empirical relationships and decipher noise or signal
Familiarity with classical statistical methods and knows when and how to apply them in a rigorous fashion
Easily learns how to apply new statistical methods
Will seek out and learn new methods to better solve problems
Constantly questions finance/trading data and stays motivated to seek answers despite most often proving that there is no correlation or signal
Experience in setup of research framework and execution of projects
Understanding of financial products, market dynamics, and microstructure
Experience programming in Low-level computer languages (like C++)
Awareness of strength in particular language and ability to solve more complex problems due to understanding nuances of the language

Nice To Haves

Experience with modern AI techniques and methods

Responsibilities

Identifying trading opportunities
Leveraging quantitative skills and coding proficiency to accelerate the innovation process
Contributing to and directly affecting the firm's bottom line
Designing new alphas
Understanding complex systems
Quickly getting into data to look for empirical relationships and decipher noise or signal
Applying classical statistical methods rigorously
Learning and applying new statistical methods
Working on Applied Machine Learning Problems
Questioning finance/trading data and seeking answers
Setting up research frameworks and executing projects
Understanding financial products, market dynamics, and microstructure
Programming in low-level computer languages (like C++)