Data Scientist, Apple Pay

Apple • Cupertino, CA

2d

About The Position

Apple is seeking an experienced Data Scientist to reimagine how Apple Pay measures and optimizes marketing. The role calls for intellectual curiosity and strategic depth, including the ability to identify important analytical questions, establish frameworks for answering them, and propose new approaches. The successful candidate will bring deep knowledge of marketing and media measurement, including marketing mix models, incremental testing, causal inference, and behavioral analytics. They will define measurement frameworks and assess causal assumptions, confounders, and experimental conditions before building models, then use AI and machine learning to deliver rigorous, scalable, and efficient measurement and insights.

Requirements

• Hands-on experience in marketing science, including marketing mix modeling, causal inference, and incremental measurement.
• Experience designing and executing marketing experiments.
• Proficiency applying machine learning techniques to marketing and customer datasets.
• Strong proficiency in Python and data science libraries such as pandas, NumPy, scikit-learn, and statsmodels, or equivalent.
• Strong command of SQL for querying and analyzing large-scale marketing and media datasets.
• Familiarity with Generative AI and large language models, and comfort integrating AI tools into analytical workflows.
• Strong written and verbal communication skills, including the ability to communicate insights with data to technical and non-technical audiences.
• Advanced degree (M.S. or Ph.D.) in Statistics, Machine Learning, Econometrics, Marketing Science, or a related quantitative field.

Nice To Haves

• Experience with paid media data across channels, including paid digital, in-store media, social, and other performance marketing platforms.
• Experience with awareness and performance marketing measurement.
• Experience applying Generative AI to marketing workflows, including budget optimization, automated creative analysis, or campaign performance reporting.

Responsibilities

• Design and implement marketing mix models and causal inference pipelines to quantify marketing effectiveness and inform budget allocation decisions.
• Build and execute incremental tests and translate results into concrete campaign recommendations.
• Apply machine learning techniques such as segmentation, propensity modeling, and behavioral pattern recognition to identify customer response patterns and inform audience strategy and experiment design.
• Partner with cross-functional teams to scope analytical problems, define success metrics, and deliver data-driven recommendations.
• Build and maintain production-grade ML models and workflows that support ongoing marketing measurement and optimization.
• Use Generative AI and LLM-based tools to accelerate insight generation, automate reporting workflows, and streamline analytical tasks.
• Communicate model outputs and experiment results to technical and non-technical audiences through visualizations, narratives, and recommendations.
• Follow trends in marketing science and media measurement and bring emerging methodologies and tools to the team.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior