As a Quantitative Research Intern, you will work side-by-side with our Research Team of mathematicians, scientists and technologists, to develop and enhance the models that drive Optiver’s trading. You will tackle a practical research project that has real-world impact and directly influences Optiver’s trading decisions. In our business, where the markets are always evolving, you will use your skills to predict its movements.
What you’ll do:
Led by our in-house education team, you will delve into trading fundamentals and engage in research projects that make a real difference. You will be paired with one of Optiver’s seasoned researchers, providing you exposure to a variety of research areas, including:
- Using statistical models and machine learning to develop trading algorithms.
- Leveraging big data technologies to analyze high-frequency trading strategies, market microstructure, and financial instruments to identify trading opportunities.
- Building stochastic models to determine the fair value of financial derivatives.
- Combining quantitative analysis and high-performance implementation to ensure the efficiency and accuracy of pricing engines and libraries.
What you’ll get:
You’ll join a culture of collaboration and excellence, surrounded by curious thinkers and creative problem-solvers. Motivated by a passion for continuous improvement, you’ll thrive in a supportive, high-performing environment alongside talented colleagues, collectively tackling some of the toughest challenges in the financial markets.
In addition, you’ll receive:
- The opportunity to work alongside best-in-class professionals from over 40 different countries
- The opportunity to earn a return internship or full-time offer in Chicago, Austin, New York City, or Amsterdam based on performance
- A highly-competitive internship compensation package
- Optiver-covered flights, living accommodations, and commuting stipends
- Extensive office perks, including breakfast, lunch and snacks, regular social events, clubs, sporting leagues and more
Who you are:
- Currently pursuing a Bachelor’s or Master’s degree in Mathematics, Statistics, Computer Science, Physics or a related STEM field with outstanding academic performance
- Expected graduation between December 2026 and June 2028
- Available to intern during Summer 2026
- Open to full-time opportunities upon graduation in 2027 or 2028
- Solid foundation in mathematics, probability, and statistics
- Excellent research, analytical, and modeling skills
- Independent research experience
- Proficiency in any programming language
- Experience in machine learning, with practical applications in time-series analysis and pattern recognition
- Strong interest in working in a fast-paced, collaborative environment
- Fluent in English with strong written and verbal communication skills
Who we are:
At Optiver, our mission is to improve the market by injecting liquidity, providing accurate pricing, increasing transparency and stabilising the market no matter the conditions. With a focus on continuous improvement, we prioritise safeguarding the health and efficiency of the markets for all participants. As one of the largest market making institutions, we are a respected partner on 100+ exchanges across the globe.
Our differences are our edge. Optiver does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, physical or mental disability, or other legally protected characteristics.
Optiver is supportive of US immigration sponsorship for this role.
*We accept one application per role per year. If you have previously applied to this position during this season and have been unsuccessful, you can reapply once the next recruitment season begins in 2026.
Below is the expected compensation for this position. This is a good-faith estimate of the base pay scale and sign-on bonus for this position and offers will ultimately be determined based on experience, education, skill set, and performance in the interview process. This position will also be eligible for the benefits listed above.