Optiver is seeking Machine Learning Researchers to join our High Frequency Trading Team. Our HFT team is comprised of Researchers and Software Engineers who focus on designing, improving and executing trading strategies using machine learning. We’re looking for someone to create and improve machine learning models, conduct signal/alpha research, and deliver improved predictions from which to run trading strategies. You’d work on a close-knit team that applies quantitative expertise and scientific training to solve tough, interdisciplinary problems.
Who we are:
Optiver is a tech-driven trading firm and leading global market maker. As one of the oldest market making institutions, we are a trusted partner of 70+ exchanges across the globe. Our mission is to constantly improve the market by injecting liquidity, providing accurate pricing, increasing transparency and acting as a stabilizing force no matter the market conditions. With a focus on continuous improvement, we participate in the safeguarding of healthy and efficient markets for everyone who participates.
Based in ‘The Domain’ neighborhood, Optiver’s Austin office serves as the firm’s innovation nucleus, with a strong focus on quantitative research, software and hardware engineering initiatives. With tech innovation an integral part of our core business, the booming city proved an ideal backdrop for our heavy investment into machine learning, research infrastructure and big data computing. What’s more, with world-class music, food and art scenes, as well as countless scenic outdoor activities, the quality of life for Austin Optiverians is second to none.
What you’ll do:
We’re looking for Machine Learning Researchers who will be versatile, flexible and creative in building and fine-tuning our ML models. As a Researcher, you’ll work on complex, high-impact projects that result in instant feedback for both your team and for the business.
- Conduct research to improve our price forecasting models using machine learning on historical data
- Collaborate with peers in reviewing research and solving problems
- Improve the research workflow to facilitate rapid innovation and increase the productivity of the team
- Participate in strategic discussions to help set the direction of our business growth
- See the direct impact of your work in production
Who you are:
- 2+ years of industry experience building applied ML models
- Experience with bringing research to production on real-world applications
- Proven experience in machine learning, deep learning, computer vision, natural language processing, reinforcement learning or a related field
- Bachelors, Masters, and/or PhD in computer science, machine learning, statistics, mathematics, physics, or a related STEM field
- Experience using Python libraries for data science and machine learning research
- Experience in computationally intensive research on very large data sets
- Thrive in a collaborative research environment
- Strong publication record in relevant conferences and journals is a plus
- This is an experienced role - current students and/or recent graduates might consider applying to our Graduate Quantitative Researcher or Quantitative Researcher Intern positions listed on our website
What you’ll get:
- Work alongside best-in-class professionals from over 40 different countries.
- Performance based bonus structure that is unmatched anywhere in the industry. We combine our profits across desks, teams and offices into a global profit pool fostering a truly collaborative environment to work in.
- Ownership over initiatives that directly solve business problems.
Alongside this you will get great other benefits such as 25 paid vacation days and market holidays, fully paid health insurance, daily breakfast and lunch, training opportunities, 401(k) match up to 50% and charitable match opportunities, regular social events and clubs, and many more.
At Optiver, we are committed to creating a diverse and inclusive environment of mutual respect. Optiver recruits, employs, trains, compensates and promotes regardless of race, religion, color, sex, gender identity, sexual orientation, age, physical or mental disability, or other legally protected characteristics.
