Sr. Quantitative Analyst, Model-Driven Pricing

Remote Full-time
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. Affirm, Inc. proudly includes Affirm, PayBright, and Returnly.

At Affirm, we are using today's technology to bring significant innovation to the financial industry. Since day one, our mission has been to deliver honest financial products that improve lives. That mission hasn’t changed — and it never will.

We’re looking for an individual to join the Merchant Pricing team! This team is responsible for enabling efficient value exchange between Affirm’s merchants, consumers, and strategic partners. As a Senior Analyst, you’ll help optimize our portfolio segments at scale and refine the analytical tooling to get us there. Your day-to-day focus will be to develop analytical capabilities to enhance our research infrastructure, and to apply your knowledge to improve Affirm’s loan economics. This is a high-impact role focused on making prudent decisions that drive profitable growth.

What you'll do
• Apply machine learning models to simulate and analyze risk on Affirm’s loan portfolio
• Ideate, validate, implement, and track performance of optimized pricing recommendations
• Build expertise in our evolving data warehouse, risk models, and optimization methodologies
• Assist in launching user-level pricing experiments and monitor against model results
• Partner with our Credit, Product, Engineering, Applied Machine Learning, Commercial, Finance and Capital Markets teams on company-wide initiatives

What we look for
• 2+ years of experience in an analytical or quantitative role
• Practical knowledge of fixed income, financial modelling, asset pricing, and consumer financial services
• Familiarity in applying Python and SQL to analyze large data sets
• Existing Github presence is a plus
• PySpark experience is a plus
• Masters Degree in Computer Science, Mathematics, Data Science, Statistics, Finance, or Financial Engineering is a plus

Location - Remote U.S.

#LI-Remote

Affirm is proud to be a remote-first company! The majority of our roles are remote and can be located anywhere in the U.S. and Canada (with the exception of the U.S. Territories, Quebec, Yukon, Nunavut, and the Northwest Territories) unless the job indicates a different global location. We are currently building operations in Spain, Poland, and Australia. Employees in remote roles have the option of working remotely or from an Affirm office in their country of hire, and may occasionally travel to an Affirm office or elsewhere for required meetings or team-building events. Our offices in Chicago, New York, Pittsburgh, Salt Lake City, San Francisco and Toronto will remain operational and accessible for anyone to use on a voluntary basis, subject to local COVID-19 guidelines.

If you got this far, we hope you're feeling excited about this role. Even if you don't feel you meet every single requirement, we still encourage you to apply. We're eager to meet people who believe in Affirm's mission and can contribute to our team in a variety of ways—not just candidates who check all the boxes.

Inclusivity:

At Affirm, People Come First is one of our core values, and that’s why diversity and inclusion are vital to our priorities as an equal opportunity employer. You can read about our D&I program here and our progress thus far in our 2020 DEI Report.

We also believe It’s On Us to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process.

By clicking "Submit Application," you acknowledge that you have read the Affirm Employment Privacy Policy, or the Affirm Employment Privacy Notice (EU) for applicants applying from the European Union, and hereby freely and unambiguously give informed consent to the collection, processing, use, and storage of your personal information as described therein.

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