Quantitative Risk Analyst (Fintech)

TL;DR

Quantitative Risk Manager (Machine Learning): Develop and oversee robust statistical models for fraud detection and credit risk under a Credit Institution license with an accent on model risk management, regulatory compliance, and AML/FT frameworks. Focus on designing independent model audits, risk monitoring, and stakeholder communication to ensure scalable and compliant risk strategies.

Location: On-site in Paris, France

Company

hirify.global is a leading European fintech product company simplifying banking and finance management for SMEs across 8 European countries, with a strong focus on customer satisfaction and AI integration.

What you will do

• Implement and enforce model risk policies as the second line of defense for all statistical models.
• Conduct independent audits of modeling studies to ensure robustness and regulatory compliance.
• Enhance AML/FT frameworks by improving transaction monitoring and fraud detection.
• Develop risk monitoring and reporting capabilities with accurate and up-to-date risk indicators.
• Collaborate and communicate model governance outcomes with diverse stakeholders across the company.

Requirements

• Must be located in Paris, France and work on-site.
• At least 3 years of experience in machine learning, statistics, or data science within banking, fintech, or insurance sectors.
• Proficiency in Python (Pandas, Scikit-learn) and strong SQL skills for data extraction.
• Solid understanding of regulatory frameworks, model risk management, and AML/FT constraints.
• Excellent stakeholder management and communication skills to explain complex model limitations.
• Autonomous and proactive mindset to build governance frameworks in a scaling organization.

Culture & Benefits

• Diverse and inclusive culture with 80+ nationalities and strong female leadership representation.
• Access to advanced AI tools to enhance work and innovation.
• Opportunity to shape model risk management in a hyper-growth fintech environment.
• Supportive management fostering technical excellence and autonomy.

Hiring process

• Interviews with Talent Acquisition Manager and future managers (1 hour each).
• Remote or live exercise to demonstrate skills and experience.
• Average process duration of 20 working days.