Data Analyst - SOx Risk

Nubank·Brazil, Sao Paulo·onsite
crypto:applicationdataIC4Risk Management
Compensation
Not disclosed
About Us Nu is one of the largest digital financial platforms in the world, with more than 122 million customers across Brazil, Mexico, and Colombia. Guided by our mission to fight complexity and empower people, we are redefining financial services in Latin America and this is still just the beginning of the purple future we're building. Listed on the New York Stock Exchange (NYSE: NU), we combine proprietary technology, data intelligence, and an efficient operating model to deliver financial products that are simple, accessible, and human. Our impact has been recognized by global rankings such as Time 100 Companies, Fast Company’s Most Innovative Companies, and Forbes World’s Best Bank. Visit our institutional page https://international.nubank.com.br/careers/ About the Team The Internal Controls SOX squad is responsible for assessing risks and testing internal controls over financial reporting across Nubank. This role will deepen our efficiency and analytics capabilities using data, automation, and AI to scale our SOX program and operational routines. You will act as a focal point to: leading complex initiatives with limited oversight, shaping how we use data/AI to run SOX more efficiently, and coaching the team on best practices in analytics and process improvement. You will be responsible for Proactively identify opportunities for process and efficiency improvements in SOX planning, testing, and reporting, using data analysis, AI and analytics tools. Design, implement, and iterate metrics and KPIs (e.g., productivity, timeliness, quality, coverage) to monitor SOX deliverables and drive decisions. Build and maintain dashboards that provide actionable insights for ICFR stakeholders (SOX team, Finance, Product BCOs, Risk, and leadership). Use SQL and other programming languages (e.g., Python ) to extract, transform, and analyze large, complex datasets from multiple sources. Experiment with and operationalize AI solutions (e.g., LLMs, code assistants,