Quantitative Researcher – Central Execution Desk

Tower Research Capital; London; On-site; GBP 70,000 - 100,000; Full time

Job summary

A leading quantitative trading firm in London is seeking a Quantitative Researcher for their Central Execution Desk. This role involves modeling market microstructure, researching execution algorithms, and improving trading models. Candidates should have a PhD or equivalent STEM degree and 3+ years of experience in electronic trading. Strong programming skills in Python and knowledge of statistical toolkits are essential for success.

Qualifications

• A minimum of 3+ years researching and building execution algorithms or TCA/market-impact models in electronic trading.
• Strong knowledge of statistical & machine-learning toolkits.
• Advanced programming skills in Python.

Responsibilities

• Modeling market microstructure using short-term alpha signals.
• Researching and improving execution algorithms from concept to production.
• Building advanced market impact and post-trade models.

Skills

Statistical analysis

Machine learning

Python programming

C++/Rust programming

Time-series analysis

Optimization

Experiment design

A/B testing

Familiarity with Linux

Version control

Education

PhD, Masters or Bachelor's degree in Mathematics, Statistics, Computer Science

Tools

Statistical & machine-learning toolkits

Time-series Databases

Job description

Quantitative Researcher – Central Execution Desk (London)

Tower Research Capital is a leading quantitative trading firm founded in 1998. Tower has built its business on a high-performance platform and independent trading teams. We have a 25+ year track record of innovation and a reputation for discovering unique market opportunities.

Tower is home to some of the world’s best systematic trading and engineering talent. We empower portfolio managers to build their teams and strategies independently while providing the economies of scale that come from a large, global organization.

Engineers thrive at Tower while developing electronic trading infrastructure at a world class level. Our engineers solve challenging problems in the realms of low-latency programming, FPGA technology, hardware acceleration and machine learning. Our ongoing investment in top engineering talent and technology ensures our platform remains unmatched in terms of functionality, scalability and performance.

At Tower, every employee plays a role in our success. Our Business Support teams are essential to building and maintaining the platform that powers everything we do — combining market access, data, compute, and research infrastructure with risk management, compliance, and a full suite of business services. Our Business Support teams enable our trading and engineering teams to perform at their best.

At Tower, employees will find a stimulating, results-oriented environment where highly intelligent and motivated colleagues inspire each other to reach their greatest potential.

Responsibilities

• Modeling market microstructure using short‑term alpha signals, order‑book dynamics and other techniques
• Researching, implementing and improving execution algorithms from concept through to production
• Building advanced market impact and post trade models
• Improving Tower’s simulation & back‑testing framework
• Working closely with traders, quant developers, and infra engineers to transition research prototypes into robust production code, monitoring, and continuous improvement loops
• Authoring research notes, dashboards, and tooling that elevate execution insight across Tower’s global trading teams

Qualifications

• A PhD (preferred), Masters or Bachelors degree from a top-tier university in Mathematics, Statistics, Computer Science, or equivalent STEM degree
• A minimum of 3+ years researching and building execution algorithms or TCA / market‑impact models in electronic trading (buy-side, sell‑side, or venue)
• Strong knowledge of statistical & machine‑learning toolkits, including time‑series analysis, optimisation, experiment design and A/B testing
• Advanced programming in Python, knowledge of C++/Rust is a plus
• Familiarity with time-series Databases, Linux and version control