Senior Staff Data Scientist, Consumer Apps - Klover

About Attain

Built for consumers and companies, alike.

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.

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.

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.

About the role

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.

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.

Attain Office Hybrid Schedule:

• Chicago, IL: 4 days in-office; 1 day remote

What a typical week might look like

• 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
• Build and improve predictive models across consumer decisioning, consumer behavior modeling, fraud, churn, transaction intelligence, and other business-critical use cases
• Own the full model development lifecycle, including data exploration, feature engineering, model training, validation, deployment, monitoring, and retraining
• Develop reusable modeling pipelines, analytical tools, and production-quality code to support scalable data science work
• Apply strong statistical and mathematical judgment to model evaluation,