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 

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 QRT’s 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.

Your future role within QRT

• Your core objective is to create high quality predictive signals.
• By leveraging access to large and diversified datasets you will identify statistical patterns and opportunities.
• Share and discuss research results, methodology, data sets and processes with other researchers.
• Implement the signals and the relevant datasets within the global execution platform.
• Monitor signal behaviour and model performance over time.
• You would lead the full strategy research cycle from signal generation to implementation.

Your present skillset

• Advanced degree in a quantitative field such as data science, statistics, mathematics, physics or engineering.
• Strong knowledge in statistics, machine learning, NLP or AI techniques is a plus.
• Capacity to multi-task in a fast paced environment while keeping strong attention to detail.
• Coding skills required in at least one leading programming language (Python, R, Matlab and /or C++, C#).
• Experience in exploring large datasets across multiple time frames is a plus.
• Intellectual curiosity to explore new data sets, solve complex problems, drive innovative processes and connect the dots between multiple fields.
• Capacity to work with autonomy within a collegial and collaborative environment.
• Strong capacity to communicate with technologists, data scientists and traders across the globe.
• Proven track record in delivering successful systematic strategies.

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.

ABOUT CUBIST

Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources.

JOB DESCRIPTION

Researchers are responsible for independently conducting quantitative finance research with a focus on statistical and predictive models. Successful researchers manage all aspects of the research process including methodology selection, data collection and analysis, testing, prototyping, backtesting, and performance monitoring.

Some successful researchers have joined us from similar backgrounds at other firms. Others have joined from related fields or directly from academia and have thrived with hands on guidance from our large team of experienced portfolio managers and researchers. Our most exceptional team members combine strong technical skills and a passion for problem solving with an intense curiosity about financial markets and human behavior.

DESIRABLE CANDIDATES

• MS or PhD candidates in finance, computer science, mathematics, physics, or other quantitative discipline
• 3-7 years of experience in alpha driven quantitative research for equities, futures, fixed income, credit, and/or FX
• Strong analytical and quantitative skills
• Demonstrated ability to conduct independent research utilizing large data sets
• Programming in any of the following: C++, Java, C#, MATLAB, R, Python, or Perl
• Detail-oriented
• Willing to take ownership of his/her work, working both independently and within a small team

We’re looking for exceptional colleagues with unparalleled passion. If you’d like your resume to stand out, tell us about your exceptional personal achievements, even if they have nothing to do with finance. Of course we love to hear more about specific engineering or data projects that you’ve worked outside of school, or as part of your curriculum. If you’re proud of the work you did we want to hear about it. In addition to exceptional statisticians and engineers, we work with talented musicians, writers, mathematicians, and founders of non-profits; we’d love to learn more about what excites you.

Job Description

This is an opportunity for students and researchers of advanced data modeling and statistical learning methods to apply these techniques to market prediction and systematic trading.

Job Responsibilities

• Pre-process (validate, clean, normalize, reduce dimension) very large data sets for model estimation and event studies
• Identify features and relationships useful for the predictive modeling of market dynamics

Desirable Candidates

• Undergraduate, MS, or PhD candidates in finance, computer science, mathematics, physics, or other quantitative discipline
• Programming in any of the following: C++, Java, C#, MATLAB, R, Python, or Perl
• Strong analytical and quantitative skills
• Demonstrated interest in financial markets and systematic trading
• Clear, concise, and proactive communicator
• Detail-oriented
• Willing to take ownership of his/her work, working both independently and within a small team

The annual base salary is $120,000-$180,000 (USD) which will be prorated based on internship start and end date. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.