Portfolio Risk Analytics Engineer (Python)

Hydrogen Group; Greater London, Liverpool, Glasgow; Hybrid; GBP 85,000 - 115,000; Full time

Job summary

Hydrogen Group is seeking an experienced Quantitative Developer to design and implement portfolio risk and performance analytics in a modern investment technology environment. You will translate complex financial models into robust, production-ready software and collaborate with platform engineers and investment stakeholders.

The role focuses on practical delivery, with hands-on coding in Python, NumPy and pandas, rigorous testing and performance optimization to support risk measurement,

Qualifications

• Strong Python programming for production-ready analytics.
• Experience translating quantitative methods into robust software.
• Experience with portfolio risk and performance analytics in production.

Responsibilities

• Develop and implement portfolio risk and performance models using Python.
• Translate quantitative methodologies into reliable, tested software.
• Build calculations for returns, volatility, covariance and risk contribution.
• Implement and validate equity and multi-asset portfolio risk models.
• Develop and maintain factor models and tracking error calculations.
• Support benchmark comparisons and portfolio performance analysis.
• Handle missing data and data-quality challenges.
• Optimize numerical calculations and improve performance.
• Create numerical tests to validate model accuracy.
• Maintain code quality with version control and peer review.

Skills

Python

NumPy

pandas

Quant modelling

Performance optimisation

Numerical testing

Tools

Git

SQL

Code reviews

Job description

Hydrogen Group is seeking an experienced Quantitative Developer to design and implement portfolio risk and performance analytics in a modern investment technology environment. You will translate complex financial models into robust, production-ready software and collaborate with platform engineers and investment stakeholders.

The role focuses on practical delivery, with hands-on coding in Python, NumPy and pandas, rigorous testing and performance optimization to support risk measurement,