EMEA Quant Trader & Researcher — High-Frequency Alphas

Trading Interview; Greater London; Hybrid; GBP 120,000 - 180,000; Full time

Benefits offered by this job

Hybrid working opportunities

Generous paid time off policies

In-office wellness experiences and gym

Job summary

Tower Research Capital, a leading quantitative trading firm with a global footprint, is seeking a Quantitative Trader/Researcher. You will design and deploy algorithmic trading strategies using Tower’s fast in-house systems, leveraging Python and C++ to analyze market data, test ideas, and refine models with a strong emphasis on rigor and scalability across asset classes.

Collaborate with trading and research teams in a results-driven environment that rewards rigorous experimentation, fast

Qualifications

• Bachelor's, master's or PhD in Mathematics, Statistics, Computer Science or equivalent STEM field.
• Experience in high-frequency or quantitative trading preferred but not required.
• Strong math and statistics background.
• Proficiency in back-testing, simulation, and statistical techniques.
• Solid data-mining and analysis skills with large tick data.
• Familiarity with signal generation and statistical models.
• Strong programming in Python and/or C++.

Responsibilities

• Design, implement, and deploy trading algorithms.
• Research high- to mid-frequency alphas.
• Analyze market data for patterns including market micro-structure and alternative data.
• Create tools to analyze data for patterns.
• Contribute to libraries of analytical computations for market data analysis and trading.
• Develop, augment, and calibrate exchange simulators.

Skills

Python

C++

Data analysis

Statistical methods

Education

Bachelor's degree in Mathematics, Statistics, Computer Science or equivalent STEM degree

PhD preferred

Tools

Back-testing frameworks

Job description

Tower Research Capital, a leading quantitative trading firm with a global footprint, is seeking a Quantitative Trader/Researcher. You will design and deploy algorithmic trading strategies using Tower’s fast in-house systems, leveraging Python and C++ to analyze market data, test ideas, and refine models with a strong emphasis on rigor and scalability across asset classes.

Collaborate with trading and research teams in a results-driven environment that rewards rigorous experimentation, fast