• Define and maintain key product indicators and a structured metrics tree to ensure consistent measurement across exchange and trading operations. • Prepare, visualize, and clearly present data needed for informed and timely decision-making. • Build informative dashboards and reports in Tableau for product, operational, and leadership teams. • Monitor product and trading performance by analyzing core metrics, feature output, execution quality, and market behavior. • Identify inefficiencies, anomalies, or risks — including suboptimal liquidity providers, algorithm behavior issues, or operational bottlenecks. • Evaluate the performance of trading algorithms and extract actionable insights to improve execution quality and profitability. • Conduct statistical and quantitative analyses, including back-tests, regressions, and time-series evaluations to validate hypotheses and support product improvements. • Perform ad-hoc deep-dive analyses based on business and operational requests. • Prepare new analytical reports and implement alerting mechanisms for key metrics and deviations. • Work closely with product and engineering teams to define analytical requirements and support a data-driven approach across the organization.

• Partner closely with two core product squads and their product managers to understand goals, define success metrics, and translate product ideas into concrete analytical plans. • Design and execute experiments on new and existing features, including scoping test populations, determining rollout strategies, and monitoring “do no harm” tests where sample sizes are smaller. • Write high-quality, efficient SQL (primarily in Snowflake via Hex) to investigate product questions, build custom analyses, and create clear, reusable queries that power reporting and decision-making. • Define tracking requirements for new features and collaborate with engineers and designers to ensure the right data is captured from day one, enabling robust analysis over the lifecycle of a feature. • Analyze experiment and feature performance data, synthesize findings into clear narratives, and make concrete, data-backed recommendations to product managers and business stakeholders (including when to roll back changes). • Collaborate closely with the analytics team (including your manager and peer analysts) for code reviews, feedback, and shared best practices, while independently driving your own roadmap and owning outcomes in your domain.

• Structure, analyze, and interpret large volumes of data, turning them into business insights. • Build and maintain interactive dashboards using tools such as Power BI, Amazon QuickSight, Google Data Studio/Analytics, and Kibana. • Support business teams in defining metrics, performance indicators (KPIs), and ad hoc analyses. • Automate reports and analysis processes using Python or R. • Identify opportunities to improve processes, pricing models, and logistics performance. • Collaborate with multidisciplinary teams (Engineering, Product, Logistics, and Commercial) to guide data-driven decisions.

• Estruturar, analisar e interpretar grandes volumes de dados, transformando-os em insights de negócio. • Construir e manter dashboards interativos em ferramentas como Power BI, Amazon QuickSight, Google Data Studio/Analytics e Kibana. • Apoiar as áreas de negócio na definição de métricas, indicadores de performance (KPIs) e análises ad hoc. • Automatizar relatórios e processos de análise utilizando Python ou R. Identificar oportunidades de melhoria em processos, modelos de pricing e performance logística. • Colaborar com equipes multidisciplinares (Engenharia, Produto, Logística e Comercial) para orientar decisões baseadas em dados.