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Quantitative Developer (C94277D)

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Hybrid

Quantitative Developer (C94277D)

Referment

Quantitative Developer (C94277D)

Skills

SQL QueriesPythonJavaSnowflakeComplianceRisk Management

1 day ago

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Important information


Contract type:

Permanent

Location:

London, UK

Work mode:

Hybrid

Published on:

18 October 2026

What they need


Referment is working with a capital-markets technology company whose software helps banks, hedge funds and asset managers trade, manage portfolios and measure risk in real time. Its Models and Quantitative Data team owns the pricing and market-risk analytics that run inside a live trading platform across every major asset class. The team is hiring a Quantitative Developer for its London office.

The Role You will design, develop and test the models that value financial positions and calculate market risk in real time. Day to day you will implement pricing and risk logic across equity, credit, FX, fixed income, commodities, crypto and their derivatives, and build the quantitative inputs those models depend on, such as yield curves, volatility surfaces and cubes, and correlation matrices.

You'll write modern, high-performance C++ for large-scale distributed systems running on a grid computing platform, and use Python, SQL and Snowflake to analyse, construct and validate model inputs. You'll also document methodologies so the models stand up to internal and external validation and compliance review. This is a hands-on engineering role with real ownership from model design through to production, working alongside other quantitative developers and data specialists.

What We're Looking For

  • Strong numerical grounding in numerical methods, linear algebra, partial differential equations, probability theory and statistics.
  • 3-5 years of large-scale C++ development and program design, with experience of data-intensive products and clean, well-tested, reusable code.
  • Familiarity with other languages such as Python, Java and SQL.
  • A strong understanding of financial derivatives, market conventions and how they are implemented.
  • Hands-on experience with financial data structures including yield curves (OIS, Libor, cross-currency), inflation curves, volatility surfaces and interest rate volatility cubes, ideally live or intraday.

Desirable

  • Experience developing risk management tools such as VaR, Monte Carlo, scenario analysis and P&L.
  • An M.S. or PhD in mathematics, physical sciences or engineering.

This could suit a quantitative developer, quantitative analyst or financial engineer working on pricing or risk libraries at a bank, hedge fund or software vendor who wants to own models end to end in a live platform. The role is based in London and is in-office, with four days a week in the office; remote work is not available.

#Referment

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