Quantitative Data Developer — Real-Time Pricing & Risk

Referment; Greater London; On-site; GBP 70,000 - 100,000; Full time

Job summary

Referment, London-based, is seeking a Quantitative Data Developer to build data solutions for pricing models and market risk in real time across asset classes. You will create robust data pipelines and analytics infrastructure, focusing on performance and reliability to deliver inputs for pricing and risk calculations.

The role emphasizes hands-on work with Python, SQL and Snowflake, data transformation, quality checks and clear documentation of data methodologies for validation.

Qualifications

• 3-5 years developing large-scale Python, writing SQL and working on 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 (OIS, Libor, cross-currency), inflation curves, volatility surfaces and interest rate volatility cubes.

Responsibilities

• Discover, design, develop and maintain data solutions that support valuation of financial positions.
• Optimize data pipelines and analytics infrastructure for performance and reliability.
• Build robust systems that deliver inputs for pricing and market-risk calculations in real time across asset classes.
• Document data methodologies clearly enough to support internal and external validation.

Skills

Python

SQL

C++/Java

Financial derivatives

Numerical methods

Education

MS or PhD in mathematics/physical sciences/engineering

Tools

Snowflake

Job description

Referment, London-based, is seeking a Quantitative Data Developer to build data solutions for pricing models and market risk in real time across asset classes. You will create robust data pipelines and analytics infrastructure, focusing on performance and reliability to deliver inputs for pricing and risk calculations.

The role emphasizes hands-on work with Python, SQL and Snowflake, data transformation, quality checks and clear documentation of data methodologies for validation.