Quantitative Researcher

Apply now

We're looking for

Quantitative Researchers

About Us

LO:TECH is a London-based venture-backed company at the forefront of digital asset trading technology. Our goal is to catalyse expansion within the entire digital asset ecosystem by serving as a powerhouse for liquidity, spanning both centralised and decentralised trading platforms.

We champion a dynamic startup atmosphere, characterised by rapid progress and immediate empowerment from the outset. Our work culture thrives on collaboration and ambition, maintaining a flat organisational structure.

With a foundation laid by founders who bring together 30 years of expertise in both traditional finance and digital asset sectors, including backgrounds in top-tier hedge funds and leading universities, LO:TECH stands at the intersection of innovation and experience.

The Role

We are in search of a Quantitative Researcher possessing exceptional analytical capabilities, as demonstrated by an advanced degree in mathematics, statistics, physics, computer science, engineering, or similar fields. A profound enthusiasm for systematic research and market microstructure is required.

Prior experience in high frequency trading is desirable and candidates who exhibit an entrepreneurial spirit and the belief that any problem, no matter its complexity, can be addressed, are highly regarded.

Preference is given to individuals who are either located in, or open to self-relocating to London, valuing the benefits of an in-person work research environment among peers with similar interests.

This position offers a distinct chance to play a pivotal role in the evolution of our core trading engine and market making strategy. You will collaborate intimately with the founding team on vital and intricate aspects of our operations, assuming responsibility for specific areas from the outset. The role affords ample opportunity for proactive engagement in shaping your duties, contributing to meaningful and enduring advancements within the company.

What you will work on

  • Research and implement various high a frequency trading and pricing strategies

  • Identify new opportunities by using statistical methods and analysing large data sets

  • Contribute to state of the art research and simulation environment, improving its tracking error with real world performance

  • Work closely with other researchers to develop and continuously improve upon mathematical models, and help translate ideas into code

Requirements

  • An advanced degree in mathematics, statistics, physics, computer science

  • Very strong research skills and experience using sophisticated mathematical tools in different contexts

  • Strong programming skills in at Python

  • Good programming skills in at least one compiled language, with an eagerness to learn Rust

  • Track record of having a scientific approach to analysing real-world problems and large amounts of empirical data (3+ year experience)

  • Strong familiarity with concurrency and OOP

  • Comfortable working with Linux/Unix, AWS, Git, Docker

We will test your technical knowledge during the interview process.

We Offer

  • Very competitive compensation

  • Highly ambitious, collaborative environment

  • Significant responsibility from day one

  • Clear path for career advancement

  • Opportunity to work directly with founding team

Our Culture

At LO:TECH we value humility in pursuit of excellence. We're curious and relaxed, but don't mistake this for lack of ambition. We're building something revolutionary and expect everyone to bring their A-game. We celebrate wins without ego and learn from setbacks without blame. If you're looking for a place where your crypto obsession is considered a professional asset rather than a distraction, you've found your home.

Location

Based in our London office

Join our Team

Want to join our team?
Then we'd love to hear from you!

LO:TECH is a digital asset trading firm. We use cutting-edge technology to provide liquidity to global markets and offer our clients innovative, valuable trading solutions.
Our website