Quantitative Researcher
Job Description & Qualification
We believe in nurturing talent to be successful and are looking for a new cohort of individuals to join the firm in the upcoming year. We will offer a stimulating, intellectual and high performing environment, where we look to work together.
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.
• Currently undertaking a PhD or Postdoctoral research program in relevant discipline.
• 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 programing 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.
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.
• Currently undertaking a PhD or Postdoctoral research program in relevant discipline.
• 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 programing 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.
Application Procedure
Please apply via our website:
https://www.qube-rt.com/careers/job?gh_jid=4104778002
https://www.qube-rt.com/careers/job?gh_jid=4104778002
About the Organization
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.
For Additional Questions
Website
Job ID
ID: J15773