Quantitative Data Developer (A15391B)

Referment; Greater London; In loco; GBP 70.000 - 120.000; Tempo pieno

Descrizione del lavoro

Referment is seeking a Quantitative Data Developer in London to design, build and maintain data solutions that underlie valuation and quantitative datasets. You will optimize pipelines, work with Python, SQL and Snowflake, and deliver robust inputs for pricing and market-risk calculations across asset classes in real time.

The role requires 3–5 years of Python/SQL experience, familiarity with C++/Java, and a solid grasp of derivatives and market conventions.

Competenze

• 3–5 years developing large-scale Python, writing SQL and working on data-intensive products.
• Experience with C++ or Java.
• Solid understanding of financial derivatives, market conventions and their implementation.

Mansioni

• Design, develop and maintain data solutions supporting valuation of financial positions and construction of quantitative datasets (curves, volatility cubes, correlation matrices).
• Optimize data pipelines and analytics infrastructure for performance and reliability; deliver inputs for pricing and market-risk calculations in real time.
• Analyse, transform and quality-check large-scale financial datasets with Python/SQL; document data methodologies for validation.

Conoscenze

Python

SQL

C++/Java

Financial derivatives knowledge

Numerical methods

Formazione

MS/PhD in mathematics or physical sciences or engineering

Strumenti

Snowflake

Descrizione del lavoro

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.