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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.
Job Responsibility:
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
Requirements:
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 we offer:
Competitive compensation & equity
Fantastic, Deeply Engaged Team
Generous vacation + Wellness days + Flex Days + holiday closure
Remote-first environment + coworking support + yearly all hands retreat
Access to coaching & growth programs
Parental top-up & leave policies
Comprehensive health benefits
Power-up budgets for books, home office setup, phone & internet, AI tools, and professional development