> Markdown version of [/jobs/ext/4699272-quantitative-data-developer-6fc382b](https://www.wearedevelopers.com/jobs/ext/4699272-quantitative-data-developer-6fc382b). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Quantitative Data Developer (6FC382B) - **Company:** Referment Limited - **Location:** Epsom, United Kingdom (Remote available) - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Java (Programming Language), C++ (Programming Language), Computer Programming, Document-Oriented Databases, Python (Programming Language), SQL Databases, Snowflake - **Published:** November 13, 2026 - **Apply:** https://www.apply4u.co.uk/jobs/quantitative-data-developer-6fc382b/55865854 ## About the Role Much of the work is hands-on with Python, SQL and Snowflake: analysing, transforming and quality-checking large-scale financial datasets so they are accurate and ready for model input. You'll also document data methodologies clearly enough to support internal and external validation. What We're Looking ForA quantitative and programming background with 3-5 years developing large-scale Python, writing SQL and working on data-intensive products. Experience with other languages such as C++ or Java. A solid understanding of financial derivatives, market conventions and their implementation. Proficiency with financial data structures such as yield curves (OIS, Libor, cross-currency), inflation curves, volatility surfaces and interest rate volatility cubes, ideally with live or intraday data. Comfort with numerical methods, linear algebra, probability theory and statistics. DesirableExperience 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 data engineer, quantitative data specialist or quantitative developer from a bank, hedge fund or software vendor who enjoys turning large financial datasets into trusted model inputs. The role is based in London and is in-office; remote work is not available. #Referment