Quantitative Risk Analyst: Python, SQL & Stress Testing

ACT Group; Amsterdam; In loco; EUR 70.000 - 90.000; Tempo pieno

Descrizione del lavoro

ACT Group is seeking a Quantitative Risk Analyst to strengthen our risk management capabilities and support financial resilience. You will develop and optimize risk models in Python, analyze large datasets with SQL, and provide data-driven insights to guide strategic decisions across the business.

You will collaborate with stakeholders and the trading desk, apply statistical techniques to identify trends, perform stress testing, and maintain robust, scalable codebases to ensure reliable risk

Competenze

• 3–5 years of relevant experience with Python and OO programming.
• Bachelor’s or Master’s degree in a quantitative field.
• Experience in trading houses is a plus.
• Strong analytical and communication skills.

Mansioni

• Design and implement advanced Python risk models.
• Optimize algorithms and statistical models for risk prediction.
• Maintain and update codebases for performance and reliability.
• Process and analyze large datasets using SQL.
• Apply statistical techniques to interpret data and identify trends.
• Perform stress testing and develop risk mitigation strategies.
• Collaborate with cross-functional teams and the trading desk to gather data and understand strategies.

Conoscenze

Python

Object-oriented programming

SQL

Risk modeling

Data analysis

Stress testing

Problem solving

Communication

Teamwork

English proficiency

Formazione

Bachelor/Master in Math/CS/Stats

Descrizione del lavoro

ACT Group is seeking a Quantitative Risk Analyst to strengthen our risk management capabilities and support financial resilience. You will develop and optimize risk models in Python, analyze large datasets with SQL, and provide data-driven insights to guide strategic decisions across the business.

You will collaborate with stakeholders and the trading desk, apply statistical techniques to identify trends, perform stress testing, and maintain robust, scalable codebases to ensure reliable risk