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

Radix Trading University Job Board; New York, Chicago (NY, IL); In loco; USD 90.000 - 130.000; Tempo pieno

Vantaggi offerti da questo lavoro

Competitive salary

Quarterly bonus based on performance

Descrizione del lavoro

Radix Trading University Job Board is seeking a full-time Quantitative Researcher based in New York. The role involves identifying trading opportunities with a focus on strong quantitative skills and coding. You'll work on diverse projects that enhance your understanding of market dynamics while directly contributing to the firm's success. Ideal candidates should possess a team mindset, a creative approach to problem-solving, and a flexible attitude towards data analysis. Competitive salary with quarterly bonuses is offered.

Competenze

• Strong quantitative skills and coding proficiency.
• Ability to quickly adapt based on new data and feedback.
• Experience in developing research frameworks.

Mansioni

• Identify trading opportunities through quantitative research.
• Work on various projects to gain insights into market dynamics.
• Collaborate with team members to innovate and improve processes.

Conoscenze

Persistent Drive to Improve

Creative Problem Solving

Team Mindset

Mental Flexibility

Orientation for Making Money

Strong intuition with data sets

Strong 'hacking' ability

Familiarity with statistical methods

Experience with AI techniques

Understanding financial products

Experience programming in C++

Descrizione del lavoro

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

Chicago, New York, Amsterdam

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.

COMPENSATION – Competitive salary, plus quarterly bonus based on individual performance and contribution towards success of others and the firm.

Qualifications

• Persistent Drive to Improve - Do you have an innate desire to rise to the next level, even after great accomplishment?
• 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.
• Team Mindset - We want people who understand 1+1 > 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.

Research / Quant trading strategy skills to have or develop

• Strong intuition and deep thinking with data sets - Designs new alphas, understands complex systems; knows where to start, or ask others where to start
• 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 problem
  • 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