Aquatic is looking for exceptional Quantitative Researchers to create and improve proprietary trading models and strategies while working closely with engineers and senior leaders across the firm. Quantitative Researchers within Aquatic work on a variety of trading strategies and research projects, with the opportunity to conduct independent research and originate research topics over time.

Specific responsibilities range from utilizing financial and other data in an effort to create or improve predictive models, developing and/or leveraging leading-edge statistical and machine-learning models to enhance the research and development system, creating algorithms to monetize the predictive signals.

Technical requirements:

• At least 4+ years of full-time professional experience
• Bachelors, Masters, PhD or Postdoc candidates in finance, computer science, mathematics, statistics, machine learning, physics, or other scientific discipline
• Solid mathematical and analytical ability; exceptional problem-solving and modeling ability
• Demonstrated ability to complete high level, statistical or applied mathematical research
• Prior experience in a quantitative role within a trading environment a plus
• Experience in solving highly complex, data intensive problems
• Programming proficiency in any of the following: Python, C++, Java or R

Behavioral requirements:

• Strong research hygiene
• Self-motivated and highly-productive, with a strong sense of ownership and urgency
• Intellectually curious, creative, and rigorous
• Excellent communication and collaboration skills
• Meticulous attention to detail
• Able to work across disciplines
• Willing to take ownership of his/her work, working both independently and within a small team
• Driven and tenacious approach with desire to build something scratch

The base salary for this role is anticipated to be between $150,000 and $300,000, which is based on information at the time of posting. This position may also be eligible for additional forms of compensation, such as a discretionary bonus, and benefits. Discretionary bonus can be a significant portion of total compensation. Actual compensation for successful candidates will be carefully determined based on a number of factors, including their unique skills, qualifications and relevant experience.

Experience Required: Entry-level (PhD Program) or Experienced (Postdoc, Faculty, Scientific Lab)

Education: PhD in Math, Science, Engineering and other relevant disciplines

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 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
 
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:

• Currently a PhD Student, Postdoc, Professor, or hold a similar advanced research position at a University
• 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