Guilherme Banhudo

- Promoted a self-serve culture with Steep, Hex, and Google Sheets, achieving 80% adoption and reducing ad-hoc reporting requests by 60%. - Implemented a Metrics Layer, standardizing business language, enhancing self-serve analytics and reducing decision turnaround time. - Established solid Data Engineering and Warehousing best practices including CI/CD pipelines, data governance, and automated testing, improving reliability and efficiency. Reduced pipeline incidents by 30% and onboarding time by 50%, while decreasing attrition and time-to-delivery, enabling scaling with fewer hires.. - Collaborated on Data Science initiatives, including demand forecasting, user segmentation, pricing optimization, driving business growth by 15%. - Led hiring and mentorship for Data Science, Analytics, and Engineering, fostering a strong data-driven culture.

- Rebuilt the MVP data platform into a production-grade system across ingestion, transformation, orchestration, presentation, and governance, improving core metric accuracy by 40%. - Built a scalable, robust, and flexible Data Platform creating a unified business view and automating workflows. - Developed web scrapers for competitor, advertising and SEO data, enhancing growth and marketing analytics. - Improved trust in analytics across the organization, accelerating adoption of self-serve reporting.

- Built a new Data Platform in Apache Airflow, Spark, and Azure Synapse, replacing an outdated SSIS-based system, resulting in a dynamic, modular architecture that improved data quality, speed and availability by 80%. - Developed a robust reporting layer in Power BI and Excel, ensuring a single source of truth with a standardized business language. - Delivered self-service BI dashboards in Power BI, reducing reporting turnaround by 40% for Finance and Operations teams. - Owned and automated key reporting processes, delivering high-quality, reliable data to internal stakeholders, external entities (JP Morgan, KPMG, Deloitte, Citibank, DoValue), and the CEO’s office. - Built and led a Data Engineering and Analytics team, establishing a data-driven culture and improving collaboration across the organization. - Managed and mentored a team of Data Analysts and Engineers, introducing agile methods and best practices. - Contributed to a data-driven culture, strengthening collaboration between business and technology teams.

Skills: Financial Analysis

One-year trainee program, comprised of two 6-month projects on different sectors. Project 1: Risk Management • Assessing and supporting the group-wide and individual Loss-Absorbing Capacity of Deferred Taxes (LACDT) under Solvency II. Project 2: Data Analysis • Asymmetrical service provider behavior identification • Per-diagnosis optimal treatment mapping (Basket Analysis)