About this role · Stem
About the Role What if your deep knowledge of credit risk frameworks could directly influence how financial institutions assess, validate, and improve their most critical models? We're looking for a Senior Credit Risk Modeler to evaluate credit scoring models, validate PD/LGD/EAD methodologies, and ensure regulatory alignment across risk-modeling workflows. This is a fully remote, flexible contract role built for seasoned quantitative professionals who want meaningful, high-impact work on their own terms. - Type: Hourly Contract - Location: Remote - Commitment: Flexible What You'll Do - Analyze credit risk models and rigorously validate their underlying assumptions - Review PD (Probability of Default), LGD (Loss Given Default), and EAD (Exposure at Default) frameworks for accuracy and completeness - Identify inconsistencies in risk scoring logic, segmentation criteria, and model architecture - Summarize model performance and pinpoint areas requiring recalibration or redesign - Assess regulatory alignment and evaluate the quality of model documentation - Support recurring reviews of credit risk datasets and scoring outputs Who You Are Must-Have: - Solid background in credit risk modeling, quantitative finance, or applied statistics - Deep, hands-on understanding of PD/LGD/EAD metrics and regulatory risk concepts - Strong analytical thinking with the ability to communicate findings clearly in writing - Proven ability to work independently and deliver structured, high-quality assessments Nice to Have: - Experience working with or within financial institutions, banks, or lending platforms - Familiarity with Basel II/III, IFRS 9, or other regulatory credit risk frameworks - Background in model validation, model risk management, or internal audit functions Why Join Us - Fully remote and flexible — work on your schedule, from anywhere - Engage with complex, intellectually stimulating credit risk challenges - Freelance autonomy with the structure of meaningful, ongoing project work - Contribute expertise that directly shapes the quality and integrity of risk models - Potential for recurring engagements as new model validation cycles launch
