Data Scientist

Description

About the Role

We are looking for a pragmatic, business-minded Data Scientist to design, build, and defend production-ready machine-learning models that power short-term lending products-from tax-refund advances to BNPL and installment loans. You'll partner with product, risk, and engineering teams to turn raw data into fair, compliant, and actionable lending insights.

What You'll Do

• Design, build, and iterate on supervised and unsupervised ML models (tree-based, regression, time-series, causal, clustering) to predict credit risk and optimize lending outcomes
• Defend model choices and validation results with statistical rigor; track AUC, KS, Gini, PSI, and CSI to monitor performance and stability
• Build reusable Python/SQL data pipelines for feature generation, model training, scoring, and reporting on ML & AI platform
• Deploy and maintain models in collaboration with peer data scientists and ML engineers, ensuring robust CI/CD and automated monitoring
• Translate model outputs into credit policy recommendations-PD calibration, reject inference, adverse-action logic, risk segmentation
• Work with risk and product teams to align decision strategies with business goals and regulatory constraints (FCRA, ECOA, etc.)
• Champion model interpretability and fairness audits; document assumptions, limitations, and controls to satisfy internal governance and external regulators

Requirements

What You'll Bring

• Bachelor's or higher degree in Mathematics, Statistics, Computer Science, or a related field
• 2+ years of industry experience in Data Science or Machine Learning
• 2+ years of hands-on experience with Python (pandas, numpy, scikit-learn, XGBoost, LightGBM)
• Strong SQL skills for large-scale data extraction and transformation
• Deep understanding of machine learning techniques including tree-based models, regression, time series, causal inference, and clustering
• Ability to quickly gain statistical insight from large, complex datasets
• Experience in credit risk, lending, or the fintech domain
• Knowledge of credit risk modeling concepts such as PD calibration, reject inference, adverse action logic, and risk segmentation
• Experience working with tax and/or credit bureau data (e.g., TransUnion, Experian, Equifax)
• Familiarity with cash-flow data as an alternative or complementary source
• Strong business acumen and problem-solving ability
• Excellent written and verbal communication skills and a collaborative mindset

Nice-to-Have

• Experience with internal ML infrastructure or similar platforms
• Familiarity with fairness and model explainability tools (e.g., SHAP, LIME)
• Exposure to short-term lending products like BNPL, tax refund advances, or POS installment loans

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All applicants applying for U.S. job openings must be legally authorized to work in the United States. Benefits are available to contract/temporary professionals, including medical, vision, dental, and life and disability insurance. Hired contract/temporary professionals are also eligible to enroll in our company 401(k) plan. Visit roberthalf.gobenefits.net for more information.

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