WallStreetQuants
New Grad Full-Time Quantitative Researcher

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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.
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.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
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.


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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.
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.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
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