Quantitative Risk Analyst

Mission

Join us as a Quantitative Risk Analyst and become the cornerstone of our model risk management strategy. You will join the Risk function, acting as the second line of defense to ensure our statistical models—from fraud detection to credit risk—are robust, compliant, and scalable as we operate under our Credit Institution license.

As a Quantitative Risk Analyst at Qonto, you will

• Act as the second line of defense: You will implement the model risk policy, inventory all models within Qonto, and assess their risk to ensure every model follows internal policy and regulation.
• Conduct independent reviews: You will perform independent audits of modeling studies led by other teams (Tech, Data) to ensure their robustness and compliance.
• Strengthen the AML/FT framework: You will improve transaction monitoring through statistical analysis to keep fraud risk low and actively detect new fraud patterns.
• Implement risk monitoring and reporting: You will help the Risk team build their monitoring capability by identifying data sources and ensuring all risk indicators are accurate and up-to-date.
• Engage stakeholders: You will align teams across the company on model governance and clearly communicate review outcomes to diverse audiences.

What you can expect

• Modern Methodologies: Work with state-of-the-art statistical techniques and modern modeling pipelines, moving away from the "old-school" approaches often found in traditional banking.
• High Impact: A unique opportunity to shape the model risk management framework from the ground up in a hyper-growth environment.
• Tech Stack: Utilization of a modern technical stack including Python and SQL, with the freedom to choose the best methodologies for the job.
• Dynamic Environment: A fast-paced setting where you will balance the thoroughness of rigorous risk analysis with the speed of execution required by our exponential client growth.

About your future manager

You will report to Gauthier, an expert in statistical modeling with a background in Data Science and Risk Management. Gauthier fosters a culture of technical excellence and autonomy, supporting you in using state-of-the-art techniques to build our risk framework from the ground up.

About You

• Experience: You have at least 3 years of experience as a Machine Learning Engineer, Statistician, or Data Scientist, with a specific background in Banking, Fintech, or Insurance (ideally in Fraud or Risk).
• Technical Mastery: You are proficient in Python (specifically libraries like Pandas and Scikit-learn) for financial modeling and have strong SQL skills for autonomous data extraction.
• Regulatory Knowledge: You have a solid understanding of regulatory frameworks (CI license), Model Risk Management, and the specific constraints of AML/FT.
• Communication: You excel at stakeholder management, capable of explaining complex model limitations and "pushing back" effectively with both technical teams and business partners.
• Builder Mindset: You are autonomous and proactive, capable of structuring governance frameworks and processes independently in a scaling organization.

On average, our hiring process lasts 20 working days. More information on our candidate journey here

Recruitment scams are on the rise. Keep in mind, we will never work with third-party platforms or agencies that request payment from candidates.

If you receive a suspicious message claiming to be from Qonto, please report it right away (support@qonto.com)