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New Grad Full-Time Quantitative Researcher

WallStreetQuants
London

Quick apply

Job details

Full-time
£145,000 - £200,000 a year

Qualifications

Rust (programming language)
Go
System design
Java
Analysis skills
C++
Bachelor's degree
Distributed systems
APIs
Communication skills
Python

Full job description

About the Role

An London-based proprietary trading firm building a research and engineering team is seeking a highly motivated Quantitative Developer to join the team as an Quantitative Researcher (QR). In this role, you will build dependable research platforms, market-data systems, and trading technology as part of the firm's quantitative engineering team.

This is an ideal opportunity for students and recent graduates who are passionate about software engineering, performance, market data, distributed systems, and quantitative finance. The work combines quantitative development, Python and C++ engineering, market data, low-latency systems, and algorithmic trading infrastructure. You will work closely with experienced traders, quantitative researchers, and engineers to learn how modern strategies, models, and trading systems are designed, tested, and implemented.

The team is small, technical, and collaborative, with direct access to experienced traders, quantitative researchers, engineers, high-quality market data, and modern research infrastructure.

This remote role is open to candidates based across Europe.

Requirements

Responsibilities

Build tools used by researchers, traders, or data teams.
Work with time-series data, APIs, and internal services.
Improve reliability, testing, and performance of research workflows.
Develop reliable software used in quantitative research, trading, simulation, and market-data workflows.
Design and maintain high-throughput data pipelines, APIs, and services for time-sensitive financial systems.
Profile latency, memory use, reliability, and performance across critical research and trading applications.
Write tests, participate in code reviews, and improve engineering standards across the codebase.
Troubleshoot production issues and build monitoring that makes failures easier to detect and diagnose.
Collaborate closely with traders and researchers to translate quantitative ideas into dependable tools.

Qualifications

Current student from any degree discipline who has developed practical programming skills.
Programming fundamentals in Python, C++, Java, or a similar language through coursework, projects, work, or self-study.
Interest in learning quantitative finance technology; no prior quant or finance experience is required.
Currently enrolled in any degree discipline and interested in building practical analytical skills.
Evidence of curiosity and problem-solving through coursework, employment, projects, competitions, hobbies, or self-study.
Strong computer science fundamentals, including data structures, algorithms, testing, and systems design.
Proficiency in Python, C++, Java, Rust, Go, or another production programming language.
Ability to reason about performance, reliability, concurrency, and operational tradeoffs.
Interest in financial markets is useful, but prior finance experience is not required.
Applicants from every degree discipline are welcome.
No prior quantitative finance, trading, or investment-industry experience is required.
Strong attention to detail, intellectual curiosity, and a commitment to continuous improvement.
Excellent communication and teamwork skills.

Ideal Candidate

The ideal candidate is a pragmatic builder who cares about correctness, performance, and maintainability. You enjoy understanding how systems behave under real load, collaborating with demanding technical users, and taking ownership from initial design through testing and production support.

Benefits

What We Offer

Hands-on development across quantitative systems, market data, research platforms, performance engineering, and production reliability.
Mentorship from experienced quantitative traders, researchers, engineers, and technologists.
Exposure to live markets, real financial datasets, and the full path from idea to implementation.
A collaborative, high-performance environment that values curiosity, discipline, and continuous learning.
Opportunities for rapid growth based on performance, ownership, and measurable impact.
Competitive compensation and a benefits package aligned with the employer and location.

Quick apply

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