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Quantitative researcher (hft)

London
Rock Bund Capital
Quantitative researcher
Posted: 19 July
Offer description

Join to apply for the Quantitative Researcher (HFT) role at Rock Bund Capital

Join to apply for the Quantitative Researcher (HFT) role at Rock Bund Capital

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Who We Are

Founded in 2019, Rock Bund Capital is a proprietary trading firm deeply committed to shaping the future of the cryptocurrency industry. We have an average daily trading volume exceeding $1 billion and peak daily trading volume reaching $5 billion. We process over 7 million transactions daily, trading more than 1,000 symbols across multiple CEx and DEx. Our CEx activity is primarily focused on top-tier platforms, where we hold the highest VIP status. In DeFi, we provide liquidity to more than 20 most popular protocols across different chains.

Who We Are

Founded in 2019, Rock Bund Capital is a proprietary trading firm deeply committed to shaping the future of the cryptocurrency industry. We have an average daily trading volume exceeding $1 billion and peak daily trading volume reaching $5 billion. We process over 7 million transactions daily, trading more than 1,000 symbols across multiple CEx and DEx. Our CEx activity is primarily focused on top-tier platforms, where we hold the highest VIP status. In DeFi, we provide liquidity to more than 20 most popular protocols across different chains.

Our team combines expertise in traditional finance, quantitative research, and advanced engineering with a deep understanding of blockchain technology. This unique blend enables us to excel in trading across complex crypto markets, including both CeFi and DeFi, while providing capital and strategic guidance to projects that drive innovation and foster sustainable growth in the crypto industry.

What You Will Do


* Research, develop and implement high frequency alpha taking /market making strategies
* Develop trading strategies, contribute to portfolio construction and multi-factor alpha blending
* Effectively use machine learning tools to model data and conduct strategy backtesting and optimization
* Responsible for the operation and risk monitoring of trading strategies

Who You Are

* Master degree in Science, Engineering or Quantitative Finance with a strong academic background
* 2-5 years of trading or research experience with high frequency quantitative strategies
* Familiar with market microstructure and backtesting systems
* Experience with mathematical and statistical modeling, strategy optimization, and able to analyze large financial data sets
* Proficient in a programming language such as Python, C++ or C, familiar with code acceleration methods, and have a good understanding of system architecture, framework and deployment
* Familiarity with network design and reducing latency would be a plus
* Experience in the development of cutting-edge machine learning techniques would be good to have
* Demonstrable passion in the digital asset space
* Creative problem solver who is intellectually curious
* Fluent in both English & Chinese to communicate effectively with colleagues across different regions
* This position is hybrid/remote

Why Join Us

* Competitive remuneration package and a meritocratic culture where accomplishments are rewarded
* Fast paced and result-oriented with a flat structure
* Teams collaborate in a casual working environment
* Excellent exposure to the digital asset ecosystem and the latest market insight
* Great career development opportunities

Disclaimer

We do not accept unsolicited resumes from any professional staffing or search firms. All resumes, or any other information identifying potential candidates, shared with any employee of Rock Bund Capital or its affiliates by any method without a standing signed supplier agreement will be deemed free to contact without restrictions, and no placement fee of any kind will be paid in the event the candidate is hired by Rock Bund Capital or any of its affiliates.


Seniority level

* Seniority level

Mid-Senior level


Employment type

* Employment type

Full-time


Job function

* Job function

Finance and Sales

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