Quantitative Analyst

Popular is seeking a Quantitative Analyst to support independent validation of quantitative models in accordance with the Model Risk Management framework and regulatory guidance. The role is responsible for evaluating models used across risk and finance functions, including credit risk, operational risk, stress testing, CECL/allowance estimation, and macroeconomic forecasting.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Mathematics, Applied Statistics, Data Science, Physics or a related quantitative field
• At least two years of experience in model development, implementation, or validation within financial services or a quantitative environment
• Experience in machine learning models is desirable
• Strong foundation in statistical modeling and machine learning techniques, including regression techniques, Random Forest, Gradient Boosting, XGBoost, neural networks, and logistic regression
• Experience applying model validation techniques, including back-testing, benchmarking, sensitivity analysis, and performance diagnostics
• Proficiency in Python, R, SAS, or similar statistical tools, as well as SQL and relational databases
• Familiarity with data ana analytics platforms such as Jupyter, AWS, Power BI, or similar tools
• Strong analytical and problem-solving skills, with the ability to manage multiple priorities and meet deadlines
• High attention to detail and ability to produce high-quality documentation
• Ability to work independently and collaboratively in a team environment
• Strong interpersonal, influencing, and stakeholder management skills
• Excellent written and verbal communication skills in English and Spanish
• Ability to translate complex quantitative concepts into clear, concise, and business-friendly language
• Strong documentation and presentation skills suitable for management