Quantitative Researcher (Full-Time - PhD+)

Radix Trading University Job Board

Chicago (IL)

On-site

USD 80,000 - 120,000

Full time

14 days+

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Job summary

A leading research-driven trading firm is seeking a Quantitative Researcher in Chicago. Ideal candidates should possess strong quantitative skills and coding capabilities to innovate trading strategies. This role provides opportunities for new insights into market dynamics and collaborative projects that impact the firm's success.

Qualifications

Strong quantitative background in math, physics, computer science, statistics, or electrical engineering.
Creative problem solver with a persistent drive to improve and collaborate with the team.
Experience in research framework setup and execution of projects.

Responsibilities

Identify trading opportunities leveraging quantitative skills and coding proficiency.
Collaborate on various projects to contribute towards trading strategies and market dynamics.
Develop new trading strategies based on statistical methods and data analysis.

Skills

Problem Solving

Quantitative Analysis

Data Interpretation

Statistical Methods

Programming (C++, Python, Java)

Education

PhD or equivalent academic background

Undergraduate degree in relevant fields

Job description

Quantitative Researcher (Full-Time - PhD+)

Chicago, Amsterdam

Please only apply to one of our Job Postings. At the bottom of the application questions below you'll have the option to indicate if there are any other roles here at Radix that you might be interested in. Please do not submit multiple applications for different positions.

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 a six-month period, you’ll gain new knowledge and insight into the fundamentals of market dynamics, trading strategies, and our proprietary research platform. We’ve stripped away the boundaries of what you can access and touch internally, 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 — professors, postdocs, PhDs, and undergraduates — not from other trading firms. We seek mental diversity and add a select group of academics each year from a wide range of disciplines.

Over the past year the new associates that joined our research team had ties to: Harvard, MIT, Cambridge, Princeton, Yale, IAS, UPenn, Stanford, Washington, UChicago, Caltech, and more.

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

Qualifications

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:

> 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

> Low-level computer languages like C++ or Python, Java, etc.; awareness of strength in particular language and ability to solve more complex problems due to understanding nuances of the language

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