• Understand business area needs and translate them into technological solutions. • Build and maintain databases for internal consumption. • Develop integrations with financial market APIs (ANBIMA, data providers, among others). • Create processes for data collection, processing, and consolidation. • Develop internal tools to support investment management. • Design automations and operational workflows using Python. • Build dashboards and analytical views to support decision-making. • Use Artificial Intelligence resources as productivity accelerators and to generate business value. • Work with large volumes of data in complex environments. • Ensure development best practices, governance, and access management.

• Partner with business stakeholders, analysts, and engineers to assess reporting needs and develop effective data solutions. • Gather and translate business requirements into data specifications, ensuring alignment with organizational goals. • Design and develop various reporting solutions, including dashboards, scorecards, and tabular data visualizations. • Create and maintain reports using SQL Server Reporting Services (SSRS) and deploy them via Visual Studio and Report Builder. • Write, optimize, and manage SQL queries to support complex reporting requirements. • Analyze report requests to ensure they meet business needs, identifying opportunities for optimization and efficiency. • Identify and eliminate redundant or unnecessary data points in reports to enhance clarity and usability. • Validate and reconcile data discrepancies across multiple sources to maintain data integrity. • Troubleshoot and resolve issues related to reports, queries, and analytics. • Maintain a catalog of existing reports and ensure proper documentation. • Conduct complex data mining exercises, interpreting results through various analytical methods. • Provide support by resolving user-reported data and reporting issues. • Offer recommendations to management for process improvements and performance metrics. • Participate in quality assurance (QA) testing and project implementation efforts.

• Oversee the performance and development of the sales support team. • Ensure efficient management of service orders, customer issues, and team inboxes to meet service level agreements. • Track and analyze orders, coaching new employees, and resolving escalated issues. • Foster a culture of continuous improvement and professional development.

• Recommend underwriting, line/limit, and policy changes to responsibly grow approvals and usage (e.g., cutoffs, segmentation, decision logic), using internal behavior, external risk signals, and reject inference techniques. • Develop cross-product customer credit profiles by connecting external credit attributes to on-us behavior, and identify signals that generalize across products vs. are product-specific. • Drive outcomes from uncovering insights in monitoring, to recommending and executing against strategic insights. • Design, execute, and analyze experiments (A/B tests, holdouts, policy tests), turning results into strategic recommendations and roll-out plans. • Intertwine analytics with business and product strategy to craft business proposals that ultimately impact the bottom-line. • Dig into user behavior and “double-clicks” of the data to identify high-impact opportunities for product improvements or targeted outreach, including second-order impacts. • Leverage AI-powered tools and techniques to accelerate analysis, develop and validate predictive insights, and push the boundaries of what’s possible in product analytics. • Share business insights and product enhancement recommendations to senior leadership and stakeholders effectively and concisely.