Graduate Quantitative Researcher, PhD

Who we are:

Optiver is a global market maker founded in Amsterdam, with offices in London, Chicago, Austin, New York, Sydney, Shanghai, Hong Kong, Singapore, Taipei and Mumbai. Established in 1986, today we are a leading liquidity provider, with close to 2,000 employees in offices around the world, united in our commitment to improve the market through competitive pricing, execution and risk management. By providing liquidity on multiple exchanges across the world in various financial instruments we participate in the safeguarding of healthy and efficient markets. We provide liquidity to financial markets using our own capital, at our own risk, trading a wide range of products: listed derivatives, cash equities, ETFs, bonds and foreign currencies.

Since its establishment in 2012, our Shanghai office is a rapidly growing participant in the Chinese markets, trading exchange-listed futures, options and equities in China mainland. Our vision is to become the trusted partner in the development of Chinese financial markets. With the culture of a start-up but the backing of a 35+ year-old trading firm, the Optiver Shanghai office is truly unique. Everyone who joins us will help shape the future of our company and its global impact. Get ready: we are only just beginning.

What you’ll do:

As a Quantitative Researcher, you’ll be responsible for the accuracy of our core pricing models and work closely with our traders to analyse and improve all facets of our trading strategies.

You’ll get to:

• Perform extensive analysis in order to implement new algorithms that support and improve our existing models.
• Develop risk management and portfolio optimisation tools to improve our execution algorithm.
• Work with petabytes of low latency, high-frequency market data sets.
• Collaborate with our developers to test and drive changes to our trading system, that will improve our ability to make successful trades.
• Keep up to date on the latest development of new models and technologies

Who you are:

• PhD degree in a highly quantitative field. Graduation time between 2023 and 2025.
• Strong knowledge of probability and statistics, experience in machine learning and time-series analysis is a big plus.
• Programming experience in any language (C, C++, Python, JAVA, etc.), ideally with a preference towards Python.
• Ability to carry a project on your own in a structured way within a short timeframe.
• Experience in working with large datasets.
• Both a self-motivated contributor and a team player, with an entrepreneurial attitude and hunger for success.
• Interest in the trading/quantitative finance industry.

Diversity, Equity and Inclusion statement

As an intentionally flat organisation, we believe that great ideas and impact can come from everyone. We are passionate about empowering individuals and creating diverse teams that thrive. Every person at Optiver should feel included, valued and respected, because we believe our best work is done together.

Our commitment to diversity and inclusion is hardwired through every stage of our hiring process. We encourage applications from candidates from any and all backgrounds, and we welcome requests for reasonable adjustments during the process to ensure that you can best demonstrate your abilities.

HOW TO APPLY

If you’re interested in taking your career to the next level and work on one of the most exciting trading floors in China mainland, apply now via the form below.

While we love how bilingual our teams are, be sure to submit the below application materials in English:

• Resume
• Academic transcripts, including Bachelors and Masters and PhD if any

For any other inquiries, please email [email protected].

PRIVACY DISCLAIMER

Optiver 重视个人信息的保护。请您在提供个人信息给我们之前，认真阅读Optiver China Privacy Notice, 了解我们如何收集及处理您的个人信息。

Personal information protection is of utmost importance to Optiver. Before you provide any personal information to us, we strongly urge you to read Optiver China Privacy Notice for acknowledging how we collect and process your personal information.