Operational Risk Data Scientist Manager

• Higher degree in mathematics, statistics, data science and engineering, or similar.
• Experience in the analysis of advanced statistical/mathematical models: fitting of statistical distributions, hypothesis testing and statistical validation, analysis of tails and extreme distributions, Monte Carlo simulations, time series analysis (traditional and advanced models).
• Knowledge of programming languages: R/Python (advanced level).
• Knowledge of database tools: SQL/SAS (advanced level).
• Handling of data in Google Cloud Service (BigQuery, Vertex AI).
• Knowledge of non-parametric models, especially for forecasting and text mining (NLP).

• Knowledge of Data Engineering and Optimization will be valued: pipeline for the processing, transformation, and consolidation of data via SQL and DBT, version control with GitLab, and efficient execution of SQL flows (DBT).

• Be part of the most innovative Bank in Western Europe, according to The Innovators awards from the American magazine Global Finance.
• Onboarding program and personalized support for your professional development.
• Individual training plan with access to our online platform, which offers an extensive catalog of self-learning resources to foster your continuous growth.
• You will have a complete health insurance plan entirely free of charge for you. In addition, you will be enrolled in the Pension Plan, to which CaixaBank will make contributions with your future in mind.
• Flexible compensation applied to transportation, training, languages, childcare, among others.
• Flexibility measures (remote work, flexible entry).
• We hold the Top Employer certification, which recognizes us as one of the best companies to work for

The Operational Risk management department aims to ensure the identification, measurement, assessment, management, mitigation, and reporting of the CaixaBank Group's operational risk.

The job location can be either in the Corporate Services in Barcelona or Madrid.

We are looking for a person capable of carrying out the analysis of large volumes of data to identify patterns and trends that may indicate potential risks, developing predictive models through the use of machine learning techniques and statistical models to predict risk events and their impact on the organization, proposing mitigation strategies to improve organizational resilience, and automating risk detection and management through technological solutions.

• Collaboration in the design and implementation of the new operational loss data model that allows for the capture of new information sources and their advanced processing through:
  • Development of predictive models through the use of machine learning techniques and statistical models to predict risk events and their impact on the organization.
  • Development and evaluation of hybrid models, which combine machine learning (ML) algorithms and advanced statistical techniques, for the estimation of operational losses, addressing challenges such as data scarcity and heterogeneity, the optimization of heavy-tailed distributions, and the estimation of extreme events.
• Collaboration in the migration of processes to Google Cloud (BigQuery, DBT, Vertex AI), designing scalable pipelines that ensure the traceability, reproducibility, and efficiency of predictive models, as well as the automation of reporting.
• Collaboration in the preparation of data for internal reporting, mainly for the Operational Risk Committee, as well as involvement in reports and communication with Senior Management, Internal Validation, Audit, and Supervisors.
• Interrelation with other management teams specialized in operational losses.

• Capacity for critical analysis and synthesis; identification of areas for improvement, and proposal of solution initiatives.
• Results-oriented and autonomous in the development of assigned tasks.
• Flexibility, anticipation, and adaptation to organizational and environmental changes.
• Good communication skills with other departments.
• Ability to build relationships and work in a team. Will require interaction with different areas of the organization.
• Own initiative and high autonomy in the development of assigned tasks.

Vision of loss databases, process analysis, liaison with internal control and non-financial risks, capacity for synthesis and analysis, implementation of anticipatory measures.