Senior Manager, Quantitative Analytics

Affirm · Remote CanadaRemotesenior

In short

▸Líder técnico de alto nivel en validación de modelos de riesgo crediticio y bajo escritura en ML.
▸Dirige un equipo de cuantitativos, haciendo validaciones profundas de modelos complejos con Python y SQL.
▸Rol único: combina liderazgo estratégico con trabajo técnico intensivo en un entorno de riesgo crítico.

Proficiency in English required for cross-functional collaboration.

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What they ask for

✓9+ años en roles técnicos como modelado, validación o análisis cuantitativo.
✓Experto en ML, riesgo crediticio y bajo escritura.
✓Dominio avanzado de Python y SQL para datasets grandes y complejos.
✓Habilidad comprobada para liderar, contratar y formar equipos cuantitativos.
✓Título en estadística, finanzas cuantitativas, matemáticas o ciencia de datos.
✓Mentalidad analítica, detallista y curiosa con enfoque en resolución de problemas.

Don't tick every box? That's normal — your free dossier shows your gaps and how to cover them in the interview.

PythonSQLMachine LearningCredit Risk ManagementUnderwritingModel ValidationData IntegrityPerformance StabilityEnterprise Risk ManagementInternal Audit

Who should you write to at Affirm?

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Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest. About Enterprise Risk & Internal Audit The Enterprise Risk & Internal Audit department protects Affirm’s operations and long-term success. We identify, assess, and monitor risk across the business. Our work includes internal audits, regulatory assurance, fraud prevention, and crisis planning. The team maintains strong controls, tracks key risk indicators, and ensures readiness for external reviews. We uphold accountability, transparency, and resilience to support responsible growth. About the Team We're looking for a sharp, driven quantitative professional to join our dynamic Model Risk Management (MRM) team. In this role, you will oversee the underwriting and credit risk validation sector - the most critical pillar of Affirm’s MRM framework. This is a unique position designed for a seasoned technical leader who can build, mentor, and manage a high-performing team while remaining deeply hands-on, personally executing validations of our most complex machine learning models. You'll collaborate across the company to shape a best-in-class risk framework, ensuring our models are robust, reliable, and ready for the future. If you're passionate about the intersection of finance, credit risk, and data science, this role is for you. What You'll Do: • Sector Leadership & Team Management: Oversee the underwriting and credit risk validation sector. Lead, mentor, and manage a team of talented quantitative professionals while setting the strategic direction for this critical risk domain. • Hands-On Model Validation: Execute rigorous, independent validations of sophisticated machine learning models across underwriting and credit risk management. • Technical Review: Evaluate conceptual soundness, data integrity, and performance stability through comprehensive testing, in-depth reviews, and continuous monitoring to ensure model accuracy. • Identification & Remediation: Detect critical model weaknesses and identify areas for improvement; collaborate with model owners and developers to track and resolve validation findings. • Framework Enhancement: Partner with cross-functional stakeholders to implement and refine the enterprise-wide Model Risk Management (MRM) framework, ensuring it remains robust and innovative. • Audit & Compliance: Coordinate with Accounting, Internal Controls, and Compliance teams to ensure all model activities meet or exceed internal standards and regulatory expectations. What We Look For: • Experience: 9+ years of professional experience in a highly technical role, such as model development, model validation, or quantitative analytics. • Domain Expertise: Deep understanding of machine learning modeling, underwriting, and credit risk management. • Technical Proficiency: Advanced ability to script in Python and expertise in using SQL to manipulate and analyze large-scale, complex datasets. • Leadership & Influence: Proven track record of hiring, managing, and mentoring quantitative teams. Ability to transition seamlessly between high-level strategic oversight and detailed, hands-on technical work. • Education: A BS, MS, or PhD in a quantitative discipline such as Statistics, Quantitative Finance, Mathematics, or Data Science. • Analytical Mindset: A natural problem-solver with a meticulous eye for detail, a deep curiosity regarding

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