We’re looking for a driven, analytically-minded professional to join the Quantitative Research team! The Quantitative Research team builds foundational models that model the user behavior at various stages in its journey within the Affirm’s ecosystem and prepare frameworks using those models to guide strategy in optimizing portfolio economics and consumer growth. 

In this role, you will be primarily focused on improving and expanding existing loan cashflow models for various different Affirm products, and support model use cases. This role also requires proactively engaging with other stakeholders around Affirm to tailor models to the needs of Credit, Merchant Pricing, Finance, Growth Analytics and other stakeholders.

The ideal candidate will have strong analytical and problem solving skills with solid knowledge of analytical tools, interpersonal skills to work cross-functionally and drive forward recommendations, and strong eagerness to identify new opportunities for modeling, optimization and improvement.  

What You'll Do

• Architect, build, refine and improve automation and research infrastructure for loan cashflow models on existing collateral and simulation frameworks for future loan originations
• Collaborate with Machine Learning and Engineering teams to implement automated model monitoring
• Deep dive into Affirm collateral performance to identify potential risks and opportunities and provide insights for different stakeholders
• Collaborate with firm-wide analytics teams to deliver analyses and tools to users across the firm
• Review implementation of models focusing on requirement verification and code quality and conduct code review for different members of the team.=

What We Look For

• 2-4  years of professional experience in a data science, modeling, or quantitative finance role
• Extensive experience with SQL and Python, or other scripting languages. Experience with Spark is a plus
• Solid background in math/statistics/finance and familiarity with quantitative research methodologies and machine learning algorithms
• Strong curiosity to learn about data, models and algorithms and proven track record in analytical and problem solving skills
• Passionate to learn about Affirm’s business and desire to understand the business context 
• Ability to collaborate and influence across different teams in the organization
• Github experience preferred. Existing github presence a plus 

Pay Grade - CAN29
Employees new to Affirm or promoted into a new role, typically begin in the min to mid range.
CAN base pay range per year:
Min: $105,300
Mid: $131,600
Max: $157,900

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