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Santander

Global retail and commercial banking group

BRA Data & Analytics Spec III

Quantitative RiskUpdated on Nov 12
Full-timeSão Paulo, State of São Paulo, BrazilNo salary listedIn-person

About the Job

Requirements

  • Deep experience in Credit Risk or Quantitative Modeling, including broad experience with IFRS 9 and Python applied to risk modeling.
  • Experience working in financial institutions.
  • Demonstrated experience implementing and sustaining models in production.
  • Knowledge of model validation, audit, and governance processes.
  • Completed undergraduate degree in Mathematics, Statistics, Physics, Engineering, Economics, Computer Science, or a related field.
  • Advanced English for reading technical documentation and interacting with global forums.

Responsibilities

  • Develop, calibrate, implement, and monitor provisioning models (IFRS 9 and CMN Resolution 4,966) and regulatory capital models (IRB), ensuring methodological robustness, computational efficiency, and regulatory compliance.
  • Develop and calibrate IFRS 9 ECL models for PD, LGD, and EAD.
  • Implement provisioning models compliant with CMN Resolution 4,966.
  • Support the development and evolution of IRB models.
  • Monitor, backtest, validate, and stress-test models.
  • Process and analyze large volumes of data.
  • Develop end-to-end automated pipelines for model execution.
  • Implement solutions in Python, PySpark, and Big Data environments.
  • Apply Artificial Intelligence, AutoML, and GenAI to automate processes and improve productivity.
  • Investigate deviations and anomalies and identify opportunities for methodological improvement.
  • Prepare technical documentation and materials for audits, validations, and regulators.
  • Support the technical development of less-experienced professionals.

Desired Qualifications

  • Postgraduate study, an MBA, or a Master's degree in quantitative fields.
  • FRM (Financial Risk Manager) certification.
  • PRM (Professional Risk Manager) certification.
  • Certifications in Data Science or Machine Learning.
  • Cloud certifications in AWS, Azure, or GCP.
  • Spanish language proficiency.
  • Knowledge of IFRS 9 and CMN Resolution 4,966 (BRGAAP); IRB; PD, LGD, EAD; Expected Credit Loss (ECL); staging and SICR; RWA; stress testing and backtesting.
  • Programming and data engineering skills in Python, PySpark, SQL, Pandas, NumPy, Git, GitFlow, clean code, design patterns, and Pytest.
  • Statistical and machine learning skills in logistic regression, GLM, GAM, survival analysis, XGBoost, LightGBM, random forest, model calibration, and AUC, Gini, and KS metrics.
  • AI and automation tools including ChatGPT, Claude, GitHub Copilot, AutoML, Optuna, Hyperopt, SHAP, LIME, Streamlit, Dash, Airflow, and Prefect; generative AI process automation; and development of agents and productivity tools.
  • Big Data and cloud technologies including Apache Spark, Databricks, Delta Lake, Parquet, AWS, Azure, S3, and EMR.

About the Company

Santander

Global retail and commercial banking group

Santander is a global bank focusing on retail and commercial banking in Europe and the Americas, serving individuals and SMEs with regional franchises and a broad consumer finance arm, plus a Corporate & Investment Banking division for multinational clients. It uses its Gravity cloud platform to migrate core banking and rapidly deploy digital services such as Openbank across markets, combining fintech-style agility with a bank's balance sheet. The bank differentiates itself by marrying a large retail footprint with global CIB capabilities under the One Santander verticals model to boost efficiency and cross-border revenue. Its goals include improving returns on tangible equity and financing the green economy through sustainable finance and renewable energy projects.

Company size
10,001+
Company stage
IPO
Headquarters
Boadilla del Monte, Spain
Founded
1902

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