Consumer finance platform using ML and nontraditional credit data for lease-to-own and credit solutions
Snap Finance operates a consumer lending platform built on React, TypeScript, Java, and PostgreSQL, with a modern data stack (Trino, Presto, Python, R, Tableau, Power BI) supporting ML-driven credit decisioning. The hiring mix is sales and marketing-heavy (48 of 77 active roles), with a secondary push in product and data roles — reflecting a shift toward scaling acquisition channels and optimizing campaign efficiency. Active projects center on attribution, experimentation frameworks, and lifecycle automation in Braze, signaling operational maturity in customer acquisition and retention metrics.
Notable leadership hires: Product Lead
Snap Finance provides lease-to-own and credit solutions to consumers across credit profiles, using machine learning and nontraditional risk variables to inform underwriting decisions. Founded in 2012, the company has built a proprietary platform that processes over a decade of consumer data and behavioral signals. The business operates across multiple channels: direct-to-consumer digital pathways, merchant partnerships, and integrated campaigns blending digital and direct mail. With 1,001–5,000 employees based primarily in Salt Lake City, Snap serves mid-market and enterprise retailers seeking white-label or integrated financing options for their customers.
React, TypeScript, Java, Spring Boot, PostgreSQL, MySQL, and MongoDB on the backend. Data stack includes Trino, Presto, Python, R, Tableau, and Power BI. Cloud infrastructure spans AWS, Azure, and GCP.
Salt Lake City, Utah. The company also hires in Costa Rica, suggesting nearshore operations or development centers outside the US.
Other companies in the same industry, closest in size