Responsibilities

• Analyze large datasets from multiple sources to form and test hypotheses about market behavior

• Research and build statistical models of financial instrument valuation and returns

• Apply statistical and machine-learning techniques to develop predictive models

• Formalize and implement systematic trading strategies by solving complex optimization problems

• Build robust and scalable quantitative research methods, tools and platforms

• Work across the research pipeline, from data extraction and analysis through model calibration, deployment and reporting

• Contribute throughout the process, from idea generation through production results
  

  
  

  Requirements
  

• Strong academic background in mathematics, machine learning, computer science, physics or a related quantitative field

• Research experience equivalent to a research-oriented master’s degree; PhD preferred

• Strong quantitative research experience within systematic trading

• Experience across idea generation, research, deployment and production analysis, with a track record of delivering meaningful results

• Strong programming skills and experience building high-quality, scalable software in Python and/or C++, ideally both

• Ability to communicate complex quantitative ideas clearly, both at a high level and in technical detail
  

  Why this Opportunity
  

• Join a newly established trading team backed by a proven global quantitative platform

• Own the full research lifecycle, from idea generation and model development through deployment and production analysis

• Work with advanced research infrastructure, large-scale datasets, and world-class engineering resources

• Collaborate directly with experienced traders, researchers, and engineers

• Have meaningful visibility and impact on strategy development and trading performance