Develop quantitative models to support risk management and decision-making across the Bank's different businesses, with the following objectives: 1) achieve the highest level of model efficiency (predictive capacity); 2) ensure models are aligned with business needs and reflect the actual risk landscape; 3) enable models to be integrated into management processes according to their usage potential, with results translated into decisions; 4) leverage available data potential during model construction; 5) execute projects according to agreed-upon timelines; 6) carry out necessary technological initiatives to deploy models into operation; 7) ensure models can be validated by the internal validation unit. To achieve this, one must thoroughly understand the data sources available within the Bank for various portfolios, be fully knowledgeable about internally used statistical techniques, and comply with relevant regulations. Additionally, the role involves proposing improvements to internal modeling processes and recommending the most suitable statistical techniques for solving specific problems. **In this role, you will have the opportunity to:** Develop new models to support credit risk management throughout all stages of a customer’s lifecycle (origination, monitoring, and collections). Propose definitions, participate in the design, and execute the development of new risk models, as well as evolutionary maintenance of existing ones. For new models, propose statistical monitoring and tracking frameworks. Comply with model development standards. Support quantitative analyses associated with integrating new models into operations. Be responsible for addressing requirements from regulators, internal auditors, or external auditors regarding model development, particularly related to methodologies under your responsibility. Actively participate in design tasks and later in testing during the technological implementation of new models or evolutionary updates to existing ones. Extract historical data from internal data servers, EDW, or other data sources. Raise data quality issues with responsible parties. Participate in executing the Bank's risk model development plan, leading or contributing to specific projects. Update the risk model inventory when a new model goes into production. Based on accumulated modeling experience, propose changes and improvements to model development standards and modeling software routines. Transfer newly developed models to the respective Operations unit. Prepare presentations for all key milestones of projects led or participated in (e.g., technical model committee, model committee, leadership meetings). Participate in all training and development activities to which you are invited. Proactively engage in self-training by researching unfamiliar statistical techniques, local and international regulations, best practices, etc. Utilize educational resources available to the team (books, journals, physical and digital articles) and contribute new materials to the rest of the team. **To succeed in this position, you need:** Civil Engineer (Industrial, Mathematics, Statistics). Experience using big data platforms for developing analytical assets. Development and implementation of risk models based on advanced analytics (machine learning). Intermediate level of SQL, Python/R