Director, Data Science & Analytics

Adobe•San Jose, CA

About The Position

The Opportunity Adobe Firefly is one of the most significant bets in Adobe's history — our generative AI platform that is redefining what creativity looks like for millions of creators and businesses worldwide. This role will be helping shape one of the most strategically important initiatives across the entire company. We are seeking a world-class Director of Data Science & Analytics to be the analytical engine behind Firefly's creator growth strategy within the Creator org. You will work at the intersection of AI product, product marketing, and advanced data science to shape how Firefly acquires, engages, and retains the next generation of creators. This is a high-visibility, high-impact role with direct and regular engagement with Adobe's C-suite and senior leadership. Your insights will be central in executive briefings, inform product roadmaps, and influence decisions that shape the future of generative AI at Adobe. If you are an experienced data scientist who thrives on high impact work, wants to operate at the frontier of AI and creativity, and is energized by influencing strategy at the highest levels of a Fortune 500 company, this role was built for you.

Requirements

12+ years of experience in data science, advanced analytics, or a related field, ideally with significant exposure to consumer product or AI-driven businesses.
A track record of operating at a senior individual contributor level, known for the depth and quality of your analytical work, and for influencing strategy well beyond your immediate team.
Demonstrated experience presenting to and influencing senior executive audiences with data-driven insights and recommendations.
Deep passion for the creator economy; you go deep to understand creators across a wide range of segments and personas.
Strong proficiency in Python and SQL for data manipulation, modeling, and analysis.
Expertise in data visualization tools like Tableau or equivalent.
Strong foundation in statistical modeling, experimentation, and lifecycle analytics.
Exceptional communication and storytelling skills — you can translate the most complex model outputs into narratives that move executives to action.
Innovative problem solver who challenges the status quo and brings fresh, creative approaches to hard problems.
Alignment with Adobe's values and a commitment to getting results through collaboration and innovation.
Comfortable operating with autonomy and leading complex projects from ideation to delivery in a highly matrixed organization.
BS degree in Computer Science, Statistics, or a related field is required, or equivalent practical experience.

Responsibilities

Drive Firefly's Growth Intelligence by serving as the definitive analytical voice for Firefly's creator growth, by defining the metrics, models, and frameworks that track Firefly's trajectory and inform its most critical strategic decisions.
Regularly present insights, forecasts, and strategic recommendations directly to Adobe's senior leadership and C-suite.
Translate complex analytical findings into clear, compelling narratives that drive executive decision-making on Firefly's biggest opportunities and risks.
Champion a culture of analytical rigor across the Firefly org. Define standards, introduce new methodologies, and inspire teams to make better decisions through data.
Develop and refine customer segmentation models to identify behavioral clusters and inform targeting strategies.
Build and maintain forecasting models to predict demand and user engagement trends.
Define and exemplify the value of customers over and develop strategies to improve it in acquisition and retention processes.
Bring rigorous data science to Firefly's go-to-market planning and campaign execution.
Identify competitive gaps, market opportunities, and return on investment levers that help Firefly win in a fast-moving generative AI landscape.
Lead churn modeling initiatives to proactively identify at-risk users and recommend mitigation strategies.
Collaborate with cross-functional teams to design experiments and interpret results, including A/B testing and cohort analyses.
Share complex modeling outcomes and insights with both technical and non-technical collaborators.