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 the job involves

• 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
• 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

Benefits

• Stock options
• Semi-annual merit increases
• Holiday bonus
• Work from anywhere
• Generous PTO
• Health & Lifestyle spending accounts
• $1000 remote office setup budget
• $5000 referral bonus
• Free KOHO Premium account
• Icon Potential Alt Text
• In-house coaching program
• $2000 annual training allowance
• Approachable leadership
• Bias towards action