PhD Quant Focus 2026

Optiver • Chicago, IL

11d • Onsite

About The Position

Fast-track your path from PhD to Quantitative Research. You’ve spent years developing rigorous hypotheses, mastering mathematical and scientific techniques and defending your findings. PhD Quant Focus is a three-day deep dive designed to show how your academic studies apply to the practical challenges of quantitative research and machine learning in global financial markets. For top performers, the program provides a fast-tracked pathway into our PhD Quantitative Research internship for the following summer. Financial markets offer one of the most complex, dynamic and data-intensive quantitative challenges. To navigate this complexity, we compress the scientific cycle to rapidly transform advanced mathematics, statistical modelling and machine learning techniques into trading algorithms that generate immediate performance outcomes. PhD Quant Focus places you directly in this research setting through hands-on workshops, practical technical discussions and direct interaction with researchers and traders who have made the transition from academia. Details Who: PhD students in STEM fields, with a preferred background or experience in machine learning (e.g., Computer Science, Statistics, Machine Learning, Electrical & Computer Engineering, Applied Mathematics) When: April 15–17, 2026 Where: Optiver’s Chicago office Travel: Flights and accommodation fully covered What you’ll do During this three-day program, you’ll work closely alongside Optiver’s quantitative researchers, traders and engineers in a series of hands-on sessions that mirror the types of problems they solve and how they approach them in practice: Participate in hands-on trading workshops Build foundational intuition around market making and quantitative decision-making and see firsthand how research connects to real-time market dynamics and trading outcomes. Work through applied quantitative research challenges Gain practical experience in applying data analysis, statistical modelling and machine learning techniques to extract signals from large-scale, noisy and event-driven data. Engage directly with experienced quantitative researchers Get insights into their day-to-day work, career paths, and tips on successfully transitioning from PhD to industry. Receive practical feedback to advance your transition to industry Get feedback on how you frame problems, reason through assumptions and communicate your thinking in an applied setting. Who you are A current PhD student in a STEM or highly quantitative discipline with interest or experience in machine learning, statistics, applied mathematics, physics or related areas. Available for a Summer 2026 or 2027 internship, with an anticipated PhD graduation between 2026 and 2029. Motivated by complex, data-intensive problems, comfortable operating in conditions of uncertainty, and confident in applying programming, mathematical modelling and data-driven methodologies to solve challenging research questions. Clear communicator of technical ideas who thrives in collaborative, multidisciplinary environments. What you'll get Direct pathway into Optiver’s PhD Quantitative Research internships High-performing participants will enter an accelerated interview process for our Summer 2027 internship, with select candidates considered for Summer 2026. Clarity on how academic research translates into applied trading impact Understand how core PhD strengths are applied, assessed and developed within Optiver’s quantitative research teams, and what strong research performance looks like in practice. Exposure to Optiver’s collaborative, multidisciplinary research culture Experience firsthand how researchers, traders, and engineers collaborate, openly share knowledge, and rapidly iterate to deliver breakthroughs at scale. A network of like-minded PhD candidates and experienced researchers Build connections with peers and team members and compare approaches, problem-solving styles and research backgrounds.

Requirements

• A current PhD student in a STEM or highly quantitative discipline with interest or experience in machine learning, statistics, applied mathematics, physics or related areas.
• Available for a Summer 2026 or 2027 internship, with an anticipated PhD graduation between 2026 and 2029.
• Motivated by complex, data-intensive problems, comfortable operating in conditions of uncertainty, and confident in applying programming, mathematical modelling and data-driven methodologies to solve challenging research questions.
• Clear communicator of technical ideas who thrives in collaborative, multidisciplinary environments.

Responsibilities

• Participate in hands-on trading workshops
• Build foundational intuition around market making and quantitative decision-making and see firsthand how research connects to real-time market dynamics and trading outcomes.
• Work through applied quantitative research challenges
• Gain practical experience in applying data analysis, statistical modelling and machine learning techniques to extract signals from large-scale, noisy and event-driven data.
• Engage directly with experienced quantitative researchers
• Get insights into their day-to-day work, career paths, and tips on successfully transitioning from PhD to industry.
• Receive practical feedback to advance your transition to industry
• Get feedback on how you frame problems, reason through assumptions and communicate your thinking in an applied setting.

Benefits

• Direct pathway into Optiver’s PhD Quantitative Research internships
• High-performing participants will enter an accelerated interview process for our Summer 2027 internship, with select candidates considered for Summer 2026.
• Clarity on how academic research translates into applied trading impact
• Understand how core PhD strengths are applied, assessed and developed within Optiver’s quantitative research teams, and what strong research performance looks like in practice.
• Exposure to Optiver’s collaborative, multidisciplinary research culture
• Experience firsthand how researchers, traders, and engineers collaborate, openly share knowledge, and rapidly iterate to deliver breakthroughs at scale.
• A network of like-minded PhD candidates and experienced researchers
• Build connections with peers and team members and compare approaches, problem-solving styles and research backgrounds.

What This Job Offers

• Career Level: Intern
• Education Level: Ph.D. or professional degree
• Number of Employees: 1,001-5,000 employees