Senior/Staff Data Scientist, Consumer Apps - Klover

<p><strong>About Attain</strong></p> <p>Built for consumers and companies, alike. </p> <p>Klover’s engineering team powers one of the fastest-growing fintech platforms in the U.S., supporting over one million active users each month. Our systems process and move more than $1.5 billion annually, enabling real-time access to financial tools, rewards, and services that help people improve their day-to-day lives.</p> <p>As part of this team, you’ll help design, build, and scale the systems that underpin Klover’s core products and platform. You’ll work on high-impact, production-grade systems that prioritize reliability, security, and performance, and that integrate with a broad ecosystem of internal and external services. The work you do will directly shape how users interact with Klover’s products, access their money, and experience transparent, low-fee financial services.</p> <p>Klover engineers collaborate closely with colleagues across backend, frontend, data science, and product teams to deliver scalable, high-quality solutions for a rapidly growing user base. You’ll have the opportunity to work with modern technologies and architectures while helping define and evolve the next generation of inclusive, data-powered financial products—building systems and interfaces that emphasize reliability, privacy, and performance at scale.</p> <p><strong>About the role</strong></p> <p>Attain is seeking a Senior/Staff Data Scientist to support the growing needs of our suite of B2C financial services. This role will be highly hands-on, focused on building, improving, validating, and deploying predictive models that power consumer decisioning and business optimization across our app portfolio.</p> <p>You will work on advanced machine learning and statistical modeling problems, including cash-flow based credit decisioning for our earned wage advance product, Klover, as well as consumer behavior modeling, transaction categorization, paycheck detection, fraud scoring, churn prediction, and other high-impact predictive modeling use cases. The ideal candidate combines strong quantitative fundamentals with practical experience building models and analytical systems from scratch.</p> <p><strong><em>Attain Office Hybrid Schedule: </em></strong></p> <ul> <li><em>Chicago, IL: </em><em>4 days in-office; 1 day remote</em></li> </ul> <p><strong>What a typical week might look like</strong></p> <ul> <li>Hands-on development of ML and statistical models at the core of our EWA product, with a focus on fast, rigorous, and high-quality execution</li> <li>Build and improve predictive models across consumer decisioning, consumer behavior modeling, fraud, churn, transaction intelligence, and other business-critical us