Credit Quantitative Researcher – Global Multi-Strategy Hedge Fund (London / New York)
Total Compensation: Circa £500,000 / $600,000 (base + bonus)
A leading global investment platform is building out its central Credit research function — an opportunity to sit at the intersection of quantitative innovation, trading strategy, and technology. Working alongside an experienced Credit PM and a world-class macro and systematic team, you’ll design and implement the next generation of analytic and signal-generation models powering cross-asset trading.
Responsibilties:
* Build and enhance Python-based pricing, valuation, and analytics libraries spanning cash bonds, CDS, and convertibles.
* Partner directly with portfolio managers to prototype and back-test alpha signals and relative-value models in Credit and Credit Derivatives.
* Develop and maintain research infrastructure, simulation environments, and backtesting frameworks used globally across trading teams.
* Create screeners, data-driven toolkits, and automation pipelines to streamline trade selection and opportunity discovery.
* Collaborate with quant devs and data engineers to onboard new datasets, integrate vendor models, and optimise real-time system performance.
Qualifications:
* Advanced degree (Master’s or PhD) in Mathematics, Physics, Engineering, Computer Science, or related technical field.
* Prior experience in a quant research, desk strat, or trading analytics role at a hedge fund or investment bank.
* Strong programming ability in Python (NumPy/Pandas/SciPy); familiarity with C++ or distributed compute frameworks advantageous.
* Experience in model-driven trading, signal research, or building systematic tools within Fixed Income or Credit markets.
* Knowledge of Credit or Convertible Bond products, valuation approaches, and derivatives fundamentals.
Please contact daniel.mclagan@stanfordblack.com for more information.
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