Quantitative Data Developer (CC5F3B5)

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

Job summary

Referment is hiring a Quantitative Data Developer for its London office to build data inputs for pricing and market-risk models. You will work on curves, volatility surfaces and data pipelines, using Python, SQL and Snowflake to prepare large financial datasets for real-time valuation across asset classes.

You will collaborate with quantitative developers to ensure robust analytics infrastructure, document methodologies, and deliver reliable datasets for internal validation and live trading

Qualifications

• 3–5 years developing large-scale Python applications.
• Experience with SQL data pipelines.
• Experience with Snowflake or cloud data platforms.
• Understanding of derivatives and market conventions.

Responsibilities

• Design, develop and maintain data solutions for valuation and datasets.
• Optimize data pipelines and analytics infrastructure for real-time pricing.
• Collaborate with quantitative developers and document methodologies.

Skills

Python

SQL

Financial data concepts

Numerical methods

Statistics

Education

MS/PhD in mathematics, physical sciences or engineering

Tools

Snowflake

C++

Java

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