Description: * Bachelor's degree in Statistics, Mathematics, Engineering, Computer Science, or related fields; * Postgraduate degree or specialization in Data Science, Statistics, Predictive Analytics, or Machine Learning, or related fields; * Proven experience in modeling and processing large volumes of data; * Experience in building predictive models and Machine Learning models; * Experience in technical leadership of analytical projects and solutions; * Leading and monitoring data-focused projects; * Practical experience with programming languages (Python, R, SQL, and similar); * Proficiency in Microsoft Office Suite (especially PowerPoint and Excel); * Experience with database management and administration tools (GCP, Databricks, AWS, SQL Server, and similar); * Knowledge of Business Intelligence (BI) data visualization tools (Tableau, Power BI, and similar); * Develop robust ETL (Extract, Transform, Load) pipelines for data preparation and statistical validation, ensuring data quality and integrity for modeling; * Define and implement data architecture and best practices for tools such as Google Cloud Platform BigQuery, focusing on optimization for statistical analysis and handling large-scale data volumes; * Develop and apply statistical models (e.g., regression, time series, classification models) to analyze large volumes of data and identify patterns, correlations, and causalities in financial outcomes; * Conduct hypothesis testing and multivariate analyses to validate business assumptions and support evidence-based decision-making grounded in solid statistical evidence; * Build and refine predictive statistical models based on internal system data and related domains within the procurement and payment processes, as well as external market databases; * Design and execute controlled experiments (e.g., A/B tests) to evaluate the impact of new strategies or automations on executive-level KPIs; * Translate complex statistical analysis results into clear, actionable business insights, presenting strategic recommendations to the Financial Directorate’s leadership; * Act as a strategic partner, participating in the formulation of new strategies and KPIs, ensuring they are measurable and statistically significant; * Collaborate with other company departments to integrate data and expand the business monitoring network (mitigating fraud and increasing operational efficiency across the Directorate’s business areas); * Provide technical guidance and support to Junior, Mid-level, and Senior Analysts in executing daily routines, ensuring data quality and effectiveness of internal operational results; * Lead the development of complex, scalable analytical solutions using statistical models, forecasting algorithms, artificial intelligence, or machine learning, where applicable; * Ensure data governance and integrity in analyses and reports, promoting standardization, best practices, and robust documentation; * Serve as the liaison between the data team and internal stakeholders, ensuring alignment between proposed solutions and business needs. 2512210202551846470