Design, develop, and optimize advanced predictive models using a broad range of statistical, machine learning, and actuarial techniques
Perform deep feature engineering, variable selection, and transformation to improve model stability, interpretability, and performance
Evaluate and compare candidate models using rigorous validation techniques
Balance model accuracy, robustness, and explainability to ensure business usability and regulatory acceptance
Apply predictive models to influence complex business problems such as pricing, risk evaluation, customer lifetime value, demand forecasting, and operational efficiency
Quantify business impact through financial metrics
Translate modeling outputs into clear recommendations and decision strategies for senior leaders
Own model documentation, assumptions, limitations, and versioning in alignment with internal governance standards
Partner with model validation, audit, and risk teams to support model reviews and respond to findings
Develop and maintain model performance monitoring frameworks
Requirements
Bachelor’s degree in Statistics, Mathematics, Economics, Actuarial Science, Data Science, or a related quantitative field
5 to 8+ years of experience in predictive modeling, advanced analytics, or actuarial modeling