Data Scientist, Apple Pay
Cupertino, CA - USA
Job Summary
We are looking for an experienced Data Scientist with the intellectual curiosity and strategic depth to reimagine how Apple Pay measures and optimizes its marketing. You dont wait to be handed a question; you identify the questions worth asking conceptualize the right framework to answer them and propose approaches that others havent considered yet. You know the marketing and media landscape deeply: how marketing mix models quantify cross-channel marketing effectiveness using statistical or econometric models how incrementally testing from geo-based experiments to causal inference methods isolates true causal lift and how behavioral signals derived from clustering propensity modeling or sequence analysis can shape smarter audience strategies and campaign design. What sets you apart is the ability to architect the right measurement framework before a single model is built identifying the causal assumptions that need to hold the confounders that need to be controlled for and the experimental conditions that will make results actionable. AI/ML is the tool you bring to take those frameworks to a level of rigor scale and speed that wouldnt otherwise be possible whether that means building production-grade causal inference pipelines designing ML-powered experiment analysis or applying LLMs to accelerate how insights are generated and communicated.
Design and implement marketing mix models and causal inference pipelines that quantify marketing effectiveness and inform budget allocation decisionsn Build and execute incrementally tests and translate results into concrete campaign recommendationsn Apply ML techniques such as segmentation propensity modeling and behavioral pattern recognition to identify customer response patterns and inform audience strategy and experiment designn Partner with cross-functional teams to scope analytical problems define success metrics and deliver data-driven recommendationsn Build and maintain production-grade ML models and workflows that support ongoing marketing measurement and optimizationn Leverage Generative AI and LLM-based tools to accelerate insight generation automate reporting workflows and streamline day-to-day analytical tasksn Communicate model outputs and experiment results clearly to both technical and non-technical audiences through visualizations narratives and recommendations
Hands-on experience in marketing science including building marketing mix models causal inference and incrementally measurementn Experience designing and executing marketing experimentsn Proficiency in applying ML techniques to marketing and customer datasetsn Strong proficiency in Python and data science libraries (pandas NumPy scikit-learn statsmodels or equivalent)n Strong command of SQL for querying and analyzing large-scale marketing and media datasetsn Familiarity with Generative AI and large language models and comfort integrating AI tools into day-to-day analytical workflowsn Strong written and verbal communication skills and are able to tell compelling stories with data to both technical and non-technical audiences
Experience with paid media data across channels paid digital in-store media social and other performance marketing platformsn Experience with awareness and performance marketing measurementn Actively follows industry trends in marketing science and media measurement aware of emerging methodologies and tools and brings those perspectives into the teamn Experience applying Generative AI to marketing workflows including budget optimization automated creative analysis or campaign performance reportingn Advanced degree (M.S. or Ph.D.) in Statistics Machine Learning Econometrics Marketing Science or a related quantitative field
Required Experience:
IC
About Company
Ask Siri to name the most successful company in the world and it might respond: Apple. And it's not just out of familial pride. Apple consistently ranks highly in profit, revenue, market capitalization, and consumer cachet. In 2018, the company became the first reach a trillion dollar ... View more