Full-time Postdoctoral Researcher

4 days ago

New York NY, New York County, NY; New York State, United States Radix Trading Full-time
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 seek mental diversity and add a select group of academics each year from a wide range of disciplines.  COMPENSATION – Competitive salary, plus quarterly bonus based on individual performance and contribution towards success of others and the firm. We’re looking for highly analytical people (math, physics, computer science, statistics, electrical engineering, etc.) who want to help build the research-driven trading firm of the future. To do that, you’ll need the following qualities: ​ Creative Problem Solving and Probabilistic Thinking
- You must enjoy learning and implementing new concepts quickly, combining knowledge from different domains to create new ideas, and take a data-driven and probabilistic approach to testing and implementing new ideas. 2 and are as committed to making the team better through sharing ideas as they are driven to improve their individual performance. Mental Flexibility & Self Awareness
- You’ll have to frequently adapt based on new data, results, and feedback on your trading ideas and your performance. Orientation for Making Money
- Although we value academic training, our work is not an academic exercise. We take a hacker’s approach to testing ideas, dropping projects that consume time without high upside, and focusing our next efforts on what will create the most value for the firm. Strong intuition and deep thinking with data sets
- Designs new alphas, understands complex systems; Demonstrates strong “hacking” ability to quickly get into data to look for empirical relationships and decipher noise or signal Experience with modern AI techniques and methods or desire to work on Applied Machine Learning Problems a plus 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