Graduate Quantitative Analyst

GRADUATE QUANTITATIVE ANALYST

London | Graduate | Full-time

About us

SilverTide is a financial markets analytics comany with offices in London and Dubai. We provide institutional hedge funds and asset managers with derivatives market research through a proprietary data and analytics platform, alongside trade execution with banks and market makers. Our clients are discretionary portfolio managers who depend on the quality of our research output.

Our quant and engineering work spans rates derivatives pricing (fixed income options and futures, vol surface calibration, synthetic data modeling), options microstructure, and fixed income analytics — P&L decomposition, relative value analysis, policy rate scenario analysis. We're a small team, so you'll work closely with sales and traders using your models.

About the role

We're hiring a graduate quantitative analyst to work on our proprietary pricing library, build tooling around it, and work directly with our proprietary market data. You'll be involved in both the mathematical/model side and the research tools that put those models in front of our clients — this isn't a purely theoretical role, and it isn't purely a coding role either. Your research and models get to clients through our proprietary platform, including an AI-driven research interface — so your work reaches PMs directly rather than sitting in a static report.

This is a fixed-term position with a route to permanent, decided at the end of the term based on fit and contribution.

Responsibilities

Develop and extend our proprietary derivatives pricing library

Work with proprietary market data to calibrate and validate models

Design and build research tools that turn quant models into usable output for our research and client-facing teams

Contribute to ongoing research on rates derivatives pricing and relative value

Requirements

Strong quantitative foundation — mathematics, physics, engineering, or a related discipline

Solid grounding in derivatives pricing theory (stochastic calculus, no-arbitrage pricing, at minimum through coursework or independent study)

Programming ability in at least one of Python or C++, strong enough to implement and test models, not just prototype in a notebook

Comfortable working with real, messy market data rather than clean textbook problems

Master's or equivalent research experience is common among successful applicants

Nice-to-haves

Familiarity with interest rate derivatives specifically (swaptions, caps/floors, SOFR/Euribor)

Exposure to vol surface calibration or model calibration more broadly

Some exposure to production-quality code (testing, version control, code review) rather than purely academic coding