Eligible candidates: Final-year PhD students or postdoctoral researchers

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped our collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors.   

Over the years, QRT has invested in a global research and execution platform which has been deployed to cover all geographies and asset classes. This platform covers a broad spectrum from high to low frequency trading systems. Our culture is centred around technology, automation, and industrialized processes. We operate in multiple languages from C++ to Python and embrace open-source software.  

Your future role within QRT 

You will join a team of quantitative researchers to learn how to design trading algorithms in a real-world data environment – a fast track to become a seasoned quantitative researcher. Surrounded by peers who have successfully transitioned from academia to applied research, you will receive mentorship from experienced professionals who will help you translate your theoretical expertise into real-world impact. The research environment at QRT is designed to be collaborative and intellectually stimulating. 

Within one of QRT's systematic teams - spanning high, mid, and low-frequencies - your core objective will be to develop high-quality predictive signals: 

• Leverage access to vast and diverse datasets to identify hidden statistical patterns and market opportunities. 

• Collaborate with fellow researchers to exchange ideas and refine methodologies. 

• Translate theoretical models into production-ready signals. 

• Lead the full research cycle - from idea generation to implementation. 

Your present skillset 

• Holding or pursuing a PhD (final year) degree in a quantitative field such as statistics, mathematics, physics, biology, computer science, or engineering. 

• A pragmatic attitude towards translating theoretical models into real-world data problems.   

• Proficiency in Python (preferred) or another leading programming language such as R, MATLAB, C++, or C#. 

• Experience working with large datasets across multiple time frames (a plus). 

• Ability to multitask in a fast-paced environment with attention to detail. 

• Intellectual curiosity to explore new data, solve complex problems, and connect ideas across disciplines. 

• Ability to work autonomously, in a collegial and collaborative setting, and with colleagues from diverse backgrounds and areas of expertise. 

• Strong communication skills. 

• Fluency in English (additional languages are a plus). 

Interviewing:   

• Apply online: All applications are reviewed by our Talent Acquisition Team, on a rolling basis. 

• Interviews: Conducted on-site or via Teams, they assess both your technical expertise and alignment with our collaborative culture. 

We invite candidates for the Quantitative Research position to take part in one of our Data Challenges. This task is designed to give you insight into the daily responsibilities of the role and allows us to assess your abilities and interest: Challenge data (ens.fr) 

QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance 

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.