• Design and execute advanced analyses on user digital behavior, campaign performance, and conversion funnels to identify patterns, opportunities, and risks. • Generate actionable insights that answer strategic business questions and translate into concrete recommendations for Marketing, Product, and Commercial teams. • Build data storytelling narratives that connect analytical findings to business decisions, tailoring the message to technical, managerial, and executive audiences. • Define KPIs, measurement frameworks, and attribution models that holistically evaluate the performance of the digital ecosystem. • Build and maintain robust data pipelines in BigQuery from sources such as GA4, CRM, media platforms, and transactional databases. • Design efficient, optimized SQL queries on large-scale tables, including Google Analytics 4 export tables (events_*). • Collaborate with Data Engineering teams on data modeling, quality, governance, and availability across GCP and AWS environments. • Design and maintain executive dashboards in Looker Studio (or other BI tools) that deliver clear, timely, and actionable information to stakeholders. • Present findings to C-level audiences, translating complex technical analyses into simple, actionable, business-oriented messages. • Document methodologies, assumptions, and analytical limitations to ensure transparency and reproducibility. • Act as a technical reference within the Analytics & Insights team, supporting junior analysts on best practices in SQL, Python, and modeling. • Collaborate with regional teams across multiple markets, understanding local nuances and consolidating learnings at a regional level. • Promote a data-driven culture, advocating for the responsible use of data and experimentation as a driver of decision-making.

• Manage and optimize GPU capacity and other compute resources across various cloud service providers to meet growing demands and ensure efficient utilization. • Build, develop, and maintain data models, reporting systems, data automation systems, dashboards, and performance metrics that support NVIDIA Infrastructure governance programs and strategic capacity decisions. • Analyze the technical and business needs for GPU capacity and other compute resources from various internal and external teams. • Identify performance bottlenecks in day-to-day usage of compute resources and collaborate with relevant infrastructure teams to resolve them. • Drive infrastructure resource efficiency initiatives in partnership with engineering, finance, and product teams. • Develop and enhance tooling for our cloud infrastructure and analytics platform to optimize resource usage and performance for NVIDIA and its customers. • This includes crafting and developing tools for automating workflows and potentially leveraging AI techniques to extract useful signals and insights from generated data. • Partner and cross-collaborate with Finance, Product, Service Owners, and Infrastructure Engineering teams to align cloud capacity management with company goals and develop Infrastructure and Service Level Key Performance Indicators (KPIs) to match Customer satisfaction. • Lead multi-year budget-based compute resource planning with engineering.

• Support supply chain operations by collecting, validating, and maintaining critical datasets required for upcoming initiatives and launches • Build, maintain, and improve Bills of Materials (BOMs) to ensure supply chain data accuracy • Develop and maintain Power BI dashboards to provide operational and supply chain insights • Analyze inconsistent or incomplete datasets and implement improvements to data quality and reliability • Coordinate changes to databases, including testing and implementation of updates • Design, implement, and maintain database structures and ETL processes to support large‑scale data needs • Write logical and physical database descriptions and define identifiers for database management systems • Modify and optimize existing databases and reporting processes as business needs evolve • Partner with technical, business, and operations stakeholders to define requirements, metrics, and reporting standards • Test data systems and reports, troubleshoot issues, and implement corrections as needed

• Support supply chain operations by collecting, validating, and maintaining critical datasets required for upcoming initiatives and launches • Build, maintain, and improve Bills of Materials (BOMs) to ensure supply chain data accuracy • Develop and maintain Power BI dashboards to provide operational and supply chain insights • Analyze inconsistent or incomplete datasets and implement improvements to data quality and reliability • Coordinate changes to databases, including testing and implementation of updates • Design, implement, and maintain database structures and ETL processes to support large‑scale data needs • Write logical and physical database descriptions and define identifiers for database management systems • Modify and optimize existing databases and reporting processes as business needs evolve • Partner with technical, business, and operations stakeholders to define requirements, metrics, and reporting standards • Test data systems and reports, troubleshoot issues, and implement corrections as needed