Quantitative Data Developer (91B96FC)

Referment; Greater London; On-site; GBP 70,000 - 110,000; Full time

Job summary

Referment is partnering with a capital-markets technology company to hire a Quantitative Data Developer for its London office. You will design and maintain data solutions used to price positions and construct quantitative datasets such as curves and volatility matrices across asset classes.

You will work hands-on with Python, SQL and Snowflake, building reliable inputs for pricing and risk calculations in real time, and you will document methodologies for validation purposes.

Qualifications

• 3–5 years developing large-scale Python, writing SQL and building data-intensive products.
• Experience with other languages such as C++ or Java.
• Solid understanding of financial derivatives, market conventions and their implementation.
• Proficiency with financial data structures such as yield curves, volatility surfaces and rate cubes.

Responsibilities

• Design, develop and maintain data solutions for valuation and quantitative datasets (curves, volatility cubes, correlations).
• Optimize data pipelines and analytics infrastructure for performance and reliability.
• Work closely with quantitative developers to deliver robust inputs for pricing and market-risk calculations in real time.

Skills

Python

SQL

C++/Java

Education

MS/PhD in math/physical sciences/engineering

Tools

Snowflake

Job description

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 builds the data that underpins pricing models and market-risk calculations inside a live trading platform across every major asset class. The team is hiring a Quantitative Data Developer for its London office.

The Role

You will discover, design, develop and maintain the data solutions that support the valuation of financial positions and the construction of quantitative datasets such as curves, volatility cubes and correlation matrices. Working closely with quantitative developers, you'll optimise data pipelines and analytics infrastructure for performance and reliability, and build robust systems that deliver inputs for pricing and market-risk calculations in real time across equity, credit, FX, fixed income, commodities, crypto and their derivatives.

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 For

• A 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.

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 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