• Support and execute the CEO’s strategic priorities through structured project management, analysis, and cross-functional coordination. • Keep the CEO informed of organizational climate, key initiatives, emerging risks, and opportunities impacting enterprise priorities. • Serve as a connective tissue between the CEO, executive leadership team, and broader organization to ensure alignment and clarity on company priorities. • Lead or coordinate cross-functional initiatives and CEO-directed projects, including developing recommendations and supporting operational execution. • Ensure the CEO and senior leaders are well-prepared for meetings by developing agendas, briefing materials, decision frameworks, and follow-up actions. • Create and assemble executive- and Board-level materials, including presentations, analyses, and briefing documents. • Support planning and content development for executive forums such as leadership meetings, All Hands, and other organizational touchpoints, in partnership with HR and Communications. • Coordinate agenda development and materials for Board meetings and ad hoc sponsor or investor requests, as applicable. • Identify opportunities to improve enterprise processes, workflows, and operating cadence for greater clarity, efficiency, and accountability. • Manage confidential and time-sensitive initiatives requiring sound judgment, discretion, and executive presence. • Travel 10–20%

• Managing and coaching a team of high performing analysts with deep subject matter expertise in their domains • Partnering and collaborating with Senior (COO, VP, Sr. Director) level leaders across the organization to build understanding of business workflows and propose requirements for KPIs and reporting tools. • Understanding impact of projects within and across workstreams, effectively proposing and defending prioritization based on business impact. • Building, testing, and iterating on stored LLM prompts and other automation tools, evangelizing the use of those tools across the data team. • Collaborate with Product, Data Science, and Engineering teams to define requirements for supporting data warehousing systems in Snowflake or our internal operating platform. • Designing data structures and tools that will scale as our company continues its adoption of LLM based analysis, including self-service conversational analytics.

• Establish strong C-level relationships during the sales cycle to understand key business objectives and metrics, instilling confidence in Adobe’s ability to deliver expected outcomes • Act as the primary liaison post-sale between customer executives and Adobe teams (Product, Legal, Engineering, Professional Services, Technical Support, TAM, and Customer Success) • Ensure a seamless transition from pre-sales requirements to post-sales execution • Develop and deliver compelling, executive-ready presentations (return on investment and total cost of ownership) to drive value realization discussions • Map current and future business processes to identify and prioritize key use cases and value drivers • Assist customers in navigating organizational changes and implementing effective change strategies • Build customer advocacy for future marketing opportunities such as case studies and events

• Lead statistical strategy across clinical programs to align with development objectives and regulatory expectations. • Provide statistical leadership for late-stage development, including pragmatic application of adaptive, Bayesian, or innovative designs where appropriate. • Draft and review SAPs, statistical components of protocols, regulatory submissions, and support regulatory interactions with global health authorities. • Mentor and develop a high-impact biostatistics team, including coaching, mentoring and performance feedback. • Collaborate with Biometrics leadership to establish, implement and enforce statistical standards, processes, and best practices. • Ensure high-quality, timely execution of statistical analyses in collaboration with cross-functional teams. • Apply advanced methodologies, including modeling and simulations to inform quantitative decision making while balancing feasibility, timelines, and scientific rigor. • Translate complex statistical concepts into clear, aligned, and decision-oriented communication for cross-functional teams and senior leadership.