Analyst II - Full Stack

November 6

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Logo of Affirm

Affirm

eCommerce • Payments • Installment Loans • Millennials • Financial Services

1001 - 5000

💰 Post-IPO Equity on 2021-01

Description

• 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. • The Credit team works cross-functionally with Machine Learning, Product, Engineering, Capital Markets, and Commercial teams to responsibly manage the risk profile of the business. • We’re looking for a thoughtful, driven individual who wants to learn, grow, and solve hard problems. • The team’s mandate is to enable sustainable growth while closely managing the profitability and resilience of our portfolio. • Come join us in our mission to change consumer finance through better data and technology, lower costs, and increased transparency while providing the best customer experience!

Requirements

• Passion and drive to change banking, payments and online marketing for the better • 3+ years work experience as a data analyst (consumer credit risk management strongly preferred but not required) • Curiosity to learn about data, models and algorithms • Extensive experience with SQL and Python • Ability to collaborate and influence across different teams in the organization • Ability to communicate findings and recommendations clearly to both technical and non-technical audiences • A passion for finding insights in data and driving change based on those insights • Grit. Lots of grit. You’ll wear 7 hats and not love all of them

Benefits

• Health care coverage - Affirm covers all premiums for all levels of coverage for you and your dependents • Flexible Spending Wallets - generous stipends for spending on Technology, Food, various Lifestyle needs, and family forming expenses • Time off - competitive vacation and holiday schedules allowing you to take time off to rest and recharge • ESPP - An employee stock purchase plan enabling you to buy shares of Affirm at a discount

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