Quantitative Researcher
LO:TECH is a capital markets firm for the onchain world, providing digital-asset market making, institutional-grade market data, analytics, and execution services. It serves institutional clients, trading firms, funds, banks, researchers, and token projects.
About LO:TECH
LO:TECH is a London-based trading business focused on onchain and digital-asset capital markets. Its proprietary high-frequency trading technology and infrastructure support liquidity provision across centralized and decentralized venues, agency execution algorithms, and institutional market-data services. The company provides live and historical tick-level crypto and prediction-market data through APIs, CSVs, websocket streams, and replay services, alongside transparent market-making dashboards and tailored enterprise data plans. Its clients include token projects, quantitative researchers, funds, banks, and other institutional market participants.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will research and implement high-frequency trading and pricing strategies. You will use statistical methods and large datasets to identify opportunities. You will improve research and simulation environments, develop mathematical models with other researchers, and translate research ideas into code.
Requirements
- Advanced degree in mathematics, statistics, physics, computer science, or a similar field
- Research experience using sophisticated mathematical tools
- Python
- A compiled programming language, preferably Rust
- 3+ years analysing real-world problems and large empirical datasets
- Experience with Linux/Unix, AWS, Git, and Docker
Responsibilities
- Research and implement high-frequency trading and pricing strategies
- Identify opportunities using statistical methods and large datasets
- Improve research and simulation environments
- Develop and improve mathematical models
- Translate research ideas into code