Data & Analytics Spec III

Responsibilities

• Build statistical and machine learning models (credit scoring, behavior scoring, etc.) for credit granting and maintenance.
• Define methodological approaches including feature engineering, algorithms, quality analysis, and performance criteria.
• Structure solutions combining analytical modeling, automation, and generative AI to transform critical processes and increase productivity.
• Collaborate with stakeholders in Risk Policy, Business, Data, and Technology to capture business needs and drive sustainable results.
• Interact with Santander Global teams to track projects and discuss new methodological approaches.
• Monitor the performance of production models, including drift, stability, and quality indicators.
• Test and propose advanced modeling techniques to improve performance and reduce lead time in model deployment.

Requirements

• Degree in Statistics, Computer Science, Physics, Mathematics, Engineering, or related quantitative fields.
• Solid knowledge and experience in advanced statistics and machine learning.
• Proficiency in SQL and Python/PySpark.
• Experience handling and manipulating large volumes of data.
• Fluency in English or Spanish for interaction with global teams.

Preferred Qualifications

• Postgraduate degree or specialization in Data Science, Credit Risk, or Project Management.
• Master's or PhD degree.
• Experience in individual (PF) or corporate (PJ) credit modeling.
• Experience with cloud environments such as Azure or GCP.
• Experience using Databricks.

About the Company

Santander is a global financial institution where innovation and adaptation drive impact. Our work touches 140 million lives every day as we reinvent ourselves for the digital age.