Design, develop, and maintain statistical and machine learning models that support high-impact business decisions across pricing, credit risk, and other areas
Actively monitor models in production, identify performance degradation or data issues, and recommend corrective actions or enhancements
Develop complex SQL and analytical code to extract, transform, and validate large, multi-source datasets used for modeling, reporting, and decision support
Perform ad hoc and exploratory analyses to address business questions, evaluate trade-offs, and inform policy or strategy decisions
Translate high-level business objectives into analytical tasks, technical specifications, and modeling approaches
Ensure data quality, consistency, and suitability for modeling; support testing, validation, and implementation activities required for production deployment

Bachelor’s degree or higher in a quantitative field (e.g., statistics, mathematics, economics, engineering, computer science, or related discipline)
3+ years of experience applying analytical and programming skills in a business or research environment
Proficiency in one or more analytical and programming languages such as Python, SQL, R, or SAS
Strong analytical problem-solving skills with the ability to apply quantitative methods creatively to business problems
Expertise in extracting, manipulating, and analyzing large-scale datasets.
Advanced proficiency in Python, SQL, and statistical tools (e.g., R, SAS) preferred.
Experience developing or supporting predictive models such as credit scorecards, pricing models, or collections strategies preferred.
Experience in financial services analytics or a related regulated, data-intensive industry preferred.
Familiarity with model performance monitoring, validation concepts, and production analytics preferred.

Senior Analyst, Predictive Analytics, Machine Learning

Key skills