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- Tasks: Model market microstructure and improve execution algorithms in a dynamic trading environment.
- Company: Join Tower Research Capital, a top quantitative trading firm with a 25-year innovation track record.
- Benefits: Enjoy a stimulating work culture, competitive salary, and opportunities for professional growth.
- Why this job: Be part of a results-driven team that values intelligence and collaboration in cutting-edge trading technology.
- Qualifications: PhD or Masters in STEM, with 3+ years in execution algorithms and strong programming skills required.
- Other info: Work closely with traders and engineers to transition research into impactful production code.
The predicted salary is between 48000 - 84000 £ per year.
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
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Quantitative Researcher – Central Execution Desk employer: Tower Research Capital
Contact Detail:
Tower Research Capital Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Researcher – Central Execution Desk
✨Tip Number 1
Familiarise yourself with the latest trends in quantitative trading and execution algorithms. Understanding current market dynamics and the technologies used in high-frequency trading can give you an edge during interviews.
✨Tip Number 2
Network with professionals in the industry, especially those working at Tower or similar firms. Attend relevant conferences, webinars, or meetups to make connections that could lead to referrals or insider information about the role.
✨Tip Number 3
Brush up on your programming skills, particularly in Python and C++. Consider working on personal projects or contributing to open-source projects that showcase your ability to build execution algorithms or market impact models.
✨Tip Number 4
Prepare to discuss your previous research and projects in detail. Be ready to explain your thought process, methodologies, and the outcomes of your work, as this will demonstrate your expertise and problem-solving abilities to the interviewers.
We think you need these skills to ace Quantitative Researcher – Central Execution Desk
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in quantitative research, execution algorithms, and any programming skills, particularly in Python. Emphasise your educational background in Mathematics, Statistics, or Computer Science.
Craft a Strong Cover Letter: Write a cover letter that showcases your passion for quantitative trading and your understanding of market microstructure. Mention specific projects or experiences that align with the responsibilities listed in the job description.
Highlight Technical Skills: Clearly outline your proficiency in statistical and machine-learning toolkits, as well as your programming capabilities. If you have experience with time-series databases or Linux, make sure to include that too.
Showcase Collaborative Experience: Since the role involves working closely with traders and engineers, provide examples of past collaborative projects. Highlight how you contributed to team success and any tools or methodologies you used to facilitate communication and project management.
How to prepare for a job interview at Tower Research Capital
✨Showcase Your Technical Skills
Make sure to highlight your programming expertise, especially in Python, and any experience with C++ or Rust. Be prepared to discuss specific projects where you've implemented execution algorithms or market-impact models.
✨Demonstrate Your Research Experience
Discuss your previous research work in detail, particularly focusing on how you've modelled market microstructure or improved execution algorithms. Use concrete examples to illustrate your problem-solving skills and innovative thinking.
✨Prepare for Technical Questions
Expect questions that test your knowledge of statistical and machine-learning concepts. Brush up on time-series analysis, optimisation techniques, and A/B testing, as these are crucial for the role.
✨Emphasise Collaboration Skills
Since the role involves working closely with traders and engineers, be ready to discuss your teamwork experiences. Highlight instances where you successfully transitioned research into production code and how you contributed to a collaborative environment.
