Data Scientist, Credit Risk

About KOHO We’re on a mission to make financial services better for every Canadian. That means no hidden fees, no predatory interest rates - just financial products designed to help our users spend smart, save more, and build real wealth. We’re a performance organization with a strong heart: we care deeply about outcomes, and everything ties back to our mission - to financially empower a generation of Canadians. At KOHO, we’re not your average 9-5. We believe real impact comes from people who are trusted, empowered, and supported to do their best work – without sacrificing their lives to do it. We prioritize work-life integration, not just work-life balance. That means asynchronous collaboration, flexible hours, and a remote-first setup built around autonomy and high trust. KOHO is entering its next chapter - leaner, smarter, more AI-integrated. We’re building for impact, not bureaucracy. If you thrive in environments that value clarity, ownership, and bold thinking, you’ll fit right in. About the Role We’re building a world-class financial product and we need someone to help take our data operations to the next level. Our team is growing fast, and we’re looking for a Predictive Modeller to join us. You understand the data-driven decision making needs of a high-growth organization and are focused on concrete outcomes and KPIs. You look for the highest leverage solution to the most important problems, through either pragmatic analysis, a predictive model, or unsupervised learning methods. What you’ll do Design and develop statistical and machine learning models for credit risk parameters (PD, EAD, LGD) across lending products including credit card, line of credit, overdraft, BNPL, etc. Execute full model development lifecycle from data exploration and feature engineering through validation and deployment Implement advanced modelling techniques including regression, classification, ensemble methods, and deep learning algorithms Conduct model performance monitoring, champion‑challenger testing, and regulatory compliance validation Collaborate with Risk Management, Credit, and Product teams to translate business requirements into technical specifications Create automated dashboards, reports, and ad‑hoc analyses to support strategic business decision‑making Document model methodology, results, and insights Lead model refresh initiatives and back‑testing procedures to maintain predictive accuracy and performance Who you are: 5+ years of experience in predictive modelling with demonstrated collaboration across data science, engineering, and product teams Proven experience developing credit risk models (PD, EAD, LGD) for consumer lending products including credit card, line of credit, overdraft, BNPL, etc. Expert proficiency in Python and SQL with hands‑on experience in feature engineering, model development, validation, and performance analysis Strong knowledge of statistical modelling techniques, machine learning algorithms, and model deployment in production environments Experience with MLOps platforms (Sagemaker) Track record of measuring and optimizing business outcomes of machine learning models in live production systems Excellent written and verbal communication skills with ability to present complex technical concepts to non‑technical stakeholders Experience with regulatory frameworks and model risk management practices in financial services Bachelor’s or Master’s degree in Statistics, Mathematics, Economics, Computer Science, or related quantitative field Passion for applying data science to improve financial products and enhance customer financial outcomes What’s in it for you? Opportunity to shape the future of fintech and financially empower a generation of Canadians Competitive compensation & equity