Data & Analytics Sr Leader
Country: Brazil
Who we are
Your story with Santander Brasil starts now. Every beginning opens a window of infinite possibilities, from the best financial decisions to the realization of dreams. Santander Brasil wants to start this journey with you.
We have been in Brazil since 1982, we are the third largest private bank in the country by assets and the only international bank with scale in national retail banking. We are a digital bank with people. We are present wherever, however and whenever you want.
Job description
By joining Santander's Regulatory Models New Generation team, you will work in the area responsible for the development, maintenance and evolution of the organization's regulatory provisioning and expected loss models, ensuring adherence to IFRS 9 and CMN Resolution 4.966 regulations.
The area's main objective is to ensure methodological robustness, regulatory compliance and sustainability of the risk models used by the Bank, in addition to driving technological and analytical evolution through the use of artificial intelligence, advanced modeling and data-driven processes.
We have a position for you as Data & Sr Leader, acting as a technical reference supporting the team's leadership, connecting strategy, regulatory modeling, innovation and people development.
Here, your role will be:
Support leadership as a specialist reference in the Provisions team of the TO-BE operating model, ensuring the development, monitoring, maintenance and evolution of regulatory risk models related to PD, LGD, EAD, ECL and Stage Allocation, ensuring compliance with IFRS 9 and Resolution 4.966 for all relevant Bank portfolios.
You will support leadership in driving the strategy of a high-performance team, working alongside business, technology, audit, validation and regulatory areas, as well as supporting the technical quality assurance of models and deliverables. A hands-on profile is expected, serving as a reference for the team on methodological, statistical and computational challenges when needed.
Among your responsibilities, you will support leadership on the following topics:
•Development and recalibration of PD, LGD and EAD parameters for regulatory and accounting purposes;
•Ensure methodological robustness of models before internal and external audits, corporate validations and regulators;
•Define and track model monitoring indicators;
•Prioritize the team's technical backlog in alignment with Risk strategy;
•Represent the area with internal stakeholders, auditors and regulators;
•Support the evolution of AI, Analytics and Model Risk Management capabilities;
•Develop people, promoting technical growth and strengthening the high-performance culture;
•Act on risk management, dependencies and deliverables of the tribe.
Required experience
•Solid experience in financial institutions and regulatory credit risk management;
•Extensive experience in Risk, Modeling or Provisions areas;
•Experience with development, validation or monitoring of IFRS 9 and Resolution 4.966 models;
•Experience working with audits, independent validations, regulators and lines of defense;
•Deep experience working with technical teams, squads or agile structures; as well as managing and developing people;
•Track record of managing complex projects and delivering strategic initiatives.
Education
•Completed degree in Statistics, Mathematics, Engineering, Economics, Computer Science, Information Systems or related fields;
•Postgraduate studies, MBA, Master's or Specialization in Risk, Quantitative Finance, Statistics, Data Science, Machine Learning or related areas.
Desirable certifications:
•Certifications in Risk Management, Modeling, Analytics or Data Science;
•Agile, Scrum or Project Management certifications;
•Certifications related to Artificial Intelligence or Machine Learning will be considered a plus.
Languages
•Advanced English for reading and defending technical models before global forums will be a plus;
•Spanish will be considered a plus.
Skills
Hard Skills
•IFRS 9 and CMN Resolution 4.966;
•PD, LGD, EAD and Expected Credit Loss (ECL) modeling;
•Stage Allocation and Stress Testing;
•Python, SQL, Spark and PySpark;
•Databricks;
•Git;
•Pandas, NumPy and Scikit-Learn;
•Statistics applied to risk modeling;
•Logistic Regression;
•Survival Analysis;
•GLM and GAM;
•Backtesting and Model Calibration;
•Machine Learning and Generative AI applications (GenAI and LLMs).
Soft Skills
•Inspiring leadership and success cases in team development;
•Hands-on profile with strong technical depth;
•Results orientation and sense of urgency;
•Ability to influence and manage stakeholders;
•Executive and technical communication;
•Strategic vision combined with high analytical rigor;
•Cross-functional collaboration and partnership building;
•Resilience to work in complex, highly demanding regulatory environments.
