Graduate Quantitative Researcher, PhD (2027 Start)

About the Role

As a Graduate Quantitative Researcher, you will tackle challenging quantitative problems in global financial markets. You will work alongside researchers, engineers, and traders to analyze large-scale datasets, develop predictive models and algorithms, and apply statistical and machine learning techniques to understand market behavior and identify trading opportunities. Research at Optiver is applied and end-to-end, involving framing research questions, testing hypotheses, developing and validating models, and seeing ideas evaluated in live market environments.

Key Responsibilities

• Participate in Global Optiver Academy, a structured onboarding program covering trading, systems, and risk management.
• Gain exposure to AI tools and technologies that support research and development.
• Develop predictive models and machine learning systems to understand market behavior and identify trading opportunities.
• Analyze large-scale market and order-flow data to uncover signals, evaluate hypotheses, and improve trading performance.
• Build and test statistical and stochastic models for pricing, forecasting, and risk management.
• Apply modern research techniques, including deep learning and AI-enabled workflows, to accelerate discovery and improve research efficiency.

Qualifications

• PhD in Statistics, Computer Science, Machine Learning, Mathematics, or a related STEM field, with outstanding academic achievements.
• Expected to graduate by mid-2027 and available to start full-time employment upon graduation.
• Solid foundation in mathematics, probability, and statistics.
• Excellent research, analytical, and modeling skills.
• Experience applying machine learning methods to real-world research problems, such as time-series analysis, prediction, forecasting, pattern recognition, optimization, or decision-making.
• Proficiency in any programming language.
• Strong interest in working in a fast-paced, collaborative environment.
• Fluent in English with strong written and verbal communication skills.

Requirements & Tech Stack

• PhD in Statistics, Computer Science, Machine Learning, Mathematics, or a related STEM field.
• Machine Learning
• Deep Learning
• Statistical and Stochastic Models
• AI-enabled workflows
• Proficiency in any programming language