Alexander Chapman
Stat Arb Quantitative Researcher

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Quantitative Researcher – Systematic Multi-Strategy (Statistical Arbitrage)
We are partnering with a leading AI-driven systematic multi-strategy hedge fund that is looking to hire an exceptional Quantitative Researcher to develop and enhance systematic trading strategies across Equities, FX, Rates, Macro, and Commodities.
In this role, you will research, design, and deploy alpha signals and systematic investment models across global markets. Working alongside world-class researchers, machine learning specialists, and engineers, you will leverage cutting-edge AI techniques, alternative datasets, and rigorous quantitative research to identify persistent market inefficiencies and build scalable, production-grade trading strategies.
What we're looking for:
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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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.
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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.
- Strong experience researching and developing systematic statistical arbitrage or quantitative trading strategies across one or more asset classes, including Equities, FX, Rates, Macro, or Commodities
- Proven track record of generating alpha through quantitative research, signal development, and portfolio construction
- Advanced quantitative, statistical, and machine learning expertise with experience developing predictive models for financial markets
- Highly proficient in Python for quantitative research, data analysis, backtesting, and production-level implementation
- Experience working with large-scale financial, alternative, and unstructured datasets to generate differentiated investment insights
- Strong understanding of market microstructure, execution, transaction costs, and risk management across systematic trading strategies
- Experience building robust research pipelines and evaluating strategies through rigorous testing, validation, and performance attribution
- Familiarity with modern AI and machine learning techniques, including supervised and unsupervised learning, feature engineering, and model optimization
- Ability to collaborate closely with researchers, engineers, and portfolio managers to translate research into live production strategies
- A curious, research-driven mindset with strong ownership across the entire research lifecycle, from idea generation through live deployment


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