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Bourne Search Ltd

Quantitative Researcher

London
Posted about 21 hours ago
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Quantitative Researcher - Must be willing to relocate to the Bahamas*

Bahamas | Proprietary Trading | Python / C++ | Machine Learning | Systematic Trading

As a Quantitative Researcher, you'll be responsible for researching, developing and implementing systematic trading strategies across global financial markets. You'll work alongside experienced researchers, software engineers and traders, leveraging large datasets, statistical modelling and machine learning techniques to identify new sources of alpha. This is a highly collaborative environment where ideas are tested rigorously and successful research moves quickly into production.

Responsibilities

  • Research and develop systematic trading strategies across global markets.
  • Analyse large financial and alternative datasets to identify predictive signals.
  • Build statistical and machine learning models.
  • Design and evaluate alpha generation ideas using robust backtesting frameworks.
  • Collaborate with software engineers to deploy research into production.
  • Continuously monitor and refine live trading models.
  • Explore new data sources and innovative research methodologies.

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.

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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.

P

Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your 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.

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It 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.

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Strong

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.

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Strong

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.

What We're Looking For

  • PhD - Strong academic background in Mathematics, Physics, Computer Science, Statistics, Engineering or a related quantitative discipline.
  • Commercial experience in quantitative research within systematic trading, proprietary trading, hedge funds or investment banking.
  • Excellent programming skills in Python, with experience in C++ being highly desirable.
  • Strong understanding of probability, statistics, optimisation and machine learning.
  • Experience working with large datasets and developing predictive models.
  • Excellent problem-solving skills with a scientific and analytical approach.

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Desirable Experience

  • Systematic futures, equities or FX trading.
  • Alpha signal research.
  • Time-series analysis.
  • Feature engineering.
  • Reinforcement learning or advanced machine learning techniques.
  • High-performance computing or distributed computing.
  • Linux environments.

Benefits

  • Housing Benefit
  • Access to company vehicles
  • Lunch provided by onsite chef
  • Use of facilities (Marina, watercraft's, cinema, gym, entertainment to name a few)
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Skills

Python
C++
Machine Learning
Systematic Trading
Statistical Modelling
Backtesting
Probability
Statistics
Optimisation
Time-series Analysis
Feature Engineering
Reinforcement Learning
High-performance Computing
Distributed Computing
Linux

Location

London, England, United Kingdom

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