Transforming B2B financing with buy now, pay later
Slope is a fintech company headquartered in SoMa, San Francisco, CA, that specializes in buy now, pay later financing solutions for B2B businesses. With $94.7 million in funding from notable investors like DoorDash and Opendoor, Slope is rapidly expanding its presence in North America and Asia, enab...
Employees at Slope enjoy competitive salaries, equity options, flexible remote work policies, and generous PTO to maintain a healthy work-life balance...
Slope fosters a culture focused on innovation and efficiency, prioritizing technology that empowers B2B businesses. The company values agility and res...
Slope • San Francisco
About Slope
Slope is building AI-driven underwriting and credit infrastructure to power the future of embedded capital. We partner with leading platforms to help small businesses access financing seamlessly at the point of need.
The Role
We are looking for a hands-on, full-stack Data Scientist to bridge the gap between raw platform sales data and pre-approval decisions. This role is central to improving how we leverage real-time merchant performance data to automate underwriting and enable instant credit access.
You will own the data science foundation that transforms noisy transactional data into actionable signals for credit decisioning. Think of the problems faced by Stripe Capital or Shopify Capital—this is the type of modeling and data product we need to build.
What You’ll Do
Build and productionize models that map sales and payment data into reliable credit signals and pre-approval pipelines.
Develop frameworks to handle fragmented, messy sales data and normalize it for underwriting use.
Partner closely with Product, Engineering, and Risk to design pre-approval strategies and continuously improve model accuracy
Conduct exploratory analyses to identify leading indicators of merchant growth, default risk, and repayment capacity.
Translate insights into tools and dashboards that underwriters and product teams can act on.
Establish best practices for experimentation, back-testing, and data validation in underwriting contexts.
What We’re Looking For
3–6+ years experience as a Data Scientist, ideally in fintech, lending, or capital products.
Hands-on experience with sales/transaction data (e.g., card processing, e-commerce, platform transaction data).
Background in underwriting, risk modeling, or capital-as-a-service products (Stripe Capital, Shopify Capital, Square Loans, etc. experience highly valued).
Strong modeling and statistical chops: ideally has developed & shipped fraud or credit risk models E2E.
Comfortable writing production-quality code (Python, SQL, ideally some familiarity with data pipelines).
A bias for action—you enjoy building MVPs and iterating quickly with stakeholders.
Excellent communication skills: able to translate technical insights into business outcomes.
Nice to Have
Experience in credit risk, merchant lending, or BNPL.
Familiarity with data architecture for high-volume transactional platforms.
Prior startup experience (0→1 or scaling phase).
Why Join Us
Chance to shape the backbone of Slope’s underwriting engine at a critical growth phase.
Work alongside a high-caliber team backed by J.P. Morgan, Sam Altman, and world-class investors.
Ownership: as the first dedicated DS IC in this area (sales-data driven underwriting), you’ll set the standard for data science in underwriting at Slope.
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