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OnePay · 22 hours ago

Staff Applied Scientist - Credit Underwritting

United States

Full-time

Remote

Senior Level, Lead/Staff

5+ years exp

OnePay is an all-in-one financial platform with a mission to improve financial access for underbanked Americans. The role of the Staff Applied Scientist involves building advanced credit and risk models to enhance lending and credit access products, leveraging machine learning and data science techniques to ensure responsible borrowing and financial well-being for millions of customers.

Responsibilities

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

Qualification

Machine LearningCredit ScoringPythonSQLStatistical ModelingModel GovernanceProactivityCollaboration

Required

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