​​Staff Applied Scientist - Credit Underwritting

OnePay is the consumer fintech trusted by millions of Americans to make money better.

Our financial system is broken. High fees, low rates, and too few ways to actually grow your money. We’re fixing it. And we’re moving fast.

We’re an all-in-one financial services platform that brings together banking, high-yield savings, credit cards, point-of-sale lending, investing, and crypto in one place. We also partner with employers, HCM providers, gig platforms, and others to deliver embedded financial services to millions of employees and frontline workers.

We’re backed by Walmart, the world’s largest retailer, and Ribbit Capital, one of fintech’s most respected investors, giving us rare scale, distribution, and the opportunity to build something truly category-defining.

But what really sets OnePay apart is how we move. Our customers don’t have time to wait… and neither do we. This place moves fast, and we’re looking for people who are:

• Ready to run

• Hungry and driven by urgency

• Exceptional at what they do, with low ego

• Comfortable operating in motion

As an Applied Scientist at OnePay, you’ll focus on building advanced credit and risk models that power OnePay’s lending and credit access products, including OnePay Advance and Overdraft. You’ll apply cutting-edge machine learning and data science techniques to design models that help expand access to affordable credit while maintaining strong risk management. Partnering closely with Product, Engineering, and Analytics, your work will directly influence how millions of Americans borrow responsibly and improve their financial well-being. You will:

• Develop and deploy real time credit scoring and risk assessment models that optimize lending decisions and expand credit access for underbanked customers.
  

• Leverage machine learning, statistical, and behavioral modeling to predict repayment patterns, creditworthiness, and affordability with fairness and transparency.
  

• Partner with Product and Engineering to integrate credit models into production systems powering products like OnePay Advance and other lending initiatives.
  

• Collaborate with Analytics, Product, and Engineering teams to monitor performance, manage model drift, and ensure responsible AI and regulatory alignment.
  

• Experiment with innovative modeling techniques—including alternative data, LLM-assisted feature engineering, and explainable AI—to continuously enhance OnePay’s credit capabilities

• 5+ years of experience building and deploying machine learning or statistical models in credit risk, lending, or financial services

• Proven expertise in credit scoring, underwriting, or loss forecasting using large-scale structured and behavioral data

• Strong technical foundation in Python, SQL, and ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch) with a deep understanding of model development and evaluation pipelines

• Experience translating complex modeling insights into actionable business and product decisions, collaborating closely with Product, Engineering, and Analytics teams.

• Familiarity with model governance, explainability, and fairness in credit decisioning and regulatory contexts (ECOA, FCRA, etc.)

• Fluency in collaborating with Product, Engineering, and Analytics teams to bring AI/ML solutions from ideation to deployment.

• Drive and proactivity – everyone here is a builder and executor.

• Competitive base salary, stock options, and health benefits from Day 1

• 401(k) plan with company match

• Remote-friendly (US), flexible time off (FTO), and opportunities for growth

• A high-growth, mission-driven, inclusive culture where your work has real impact

• Initial Interview with Talent Partner

• Technical or Hiring Manager Interview

• Team Interview

• Executive Interview

• Offer!

To build technology and products that are used and loved by people and solve real-world problems, we need to build a team with many different perspectives and experiences. We are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We encourage candidates from all backgrounds to apply. Applicants in need of special assistance or accommodation during the interview process or in accessing our website may contact us at [email protected].