Optiver is proud to sponsor ICML 2026 in Seoul. Visit us to learn more about our work in ML, decode complex puzzles in our Cipher Challenge, and connect with researchers and engineers from across our global offices.
Global financial markets are vast, complex systems that generate enormous amounts of data and evolve continuously. Our researchers transform scientific hypotheses into algorithmic trading strategies, using immediate market feedback to test, refine and improve performance.
Each iteration sharpens our edge, improving trading 24 hours a day, across hundred of exchanges, and millions of instruments worldwide.
Many of the challenges we work on begin with ideas rooted in mathematics, statistics, and machine learning. Researchers and engineers work side by side to translate these ideas into models and systems that operate at scale in real-world environments.
| Research Area | Example application |
|---|---|
| Stochastic, Statistical modelling and Probability | Pricing models, Forecasting |
| Machine learning and Time-series Forecasting | Predictive modelling, Signal discovery |
| Reinforcement learning and Optimal Control | Decision-making under uncertainty |
| NLP and Multimodal Learning | Extracting signals from noisy and unstructured data |
| Large-scale experimentation and High-Performance Computing | Model training, Validation and Inference |
Watch this video to hear how Optiver researchers turn scientific hypotheses into production systems, from developing and testing new ideas to deploying models in fast-moving, real-world environments.
We trade with our own capital. Without client constraints or lengthy product cycles, you're free to to move quickly from hypothesis to implementation. Backed by substantial R&D investment, you'll be empowered to explore bigger challenges with greater impact.
Interested in applying research to complex, real-world systems? Explore open opportunities across our global offices.
