Responsibilities

• Identify questions worth asking and architect the ideal measurement frameworks before models are built.
• Leverage AI and ML to elevate frameworks with rigor, scale, and speed; build production-grade causal inference pipelines and ML-powered experiment analyses.
• Apply Large Language Models to accelerate how insights are generated and communicated.
• Reimagine how Apple Pay measures and optimizes marketing through strategic data science leadership.
• Collaborate with cross-functional teams to translate data into decision-ready recommendations.

Requirements

• Hands-on experience in marketing science, including building marketing mix models, causal inference, and incrementality measurement.
• Proven experience designing and executing rigorous marketing experiments.
• Demonstrated proficiency in applying ML techniques to large-scale marketing and customer datasets.
• Strong programming skills in Python and data science libraries (pandas, NumPy, scikit-learn, statsmodels).
• Advanced SQL for querying, manipulating, and analyzing massive marketing and media datasets.
• Familiarity with Generative AI and large language models, with comfort integrating AI tools into daily analytics workflows.
• Exceptional written and verbal communication skills to tell data-driven stories to diverse stakeholders.

Preferred

• Experience analyzing paid media data across channels including paid digital, in-store media, social, and other performance platforms.
• Deep understanding of both awareness and performance marketing measurement.
• Track record of following industry trends in marketing science and media measurement and bringing emerging methodologies to the team.
• Experience applying Generative AI to marketing workflows such as budget optimization or automated campaign reporting.
• Advanced degree (M.S. or Ph.D.) in Statistics, ML, Econometrics, Marketing Science, or related field.