Data Scientist, Apple Pay Marketing (Machine Learning Research)

Apple is where individual imaginations gather committing to values that lead to great work. Every new product we build service we create or Apple Store experience we deliver is the result of us making each others ideas stronger. This happens because every one of us shares a belief that we can make something wonderful and share it with the world changing lives for the better. Its the diversity of our people and their thinking that inspires the innovation running through everything we do. When we bring everybody in we can do the best work of our lives. nnHere youll do more than join something; youll add something. At Apple extraordinary ideas have a way of becoming great products services and customer experiences very quickly.

We are seeking an experienced Data Scientist with the intellectual curiosity and strategic depth to reimagine how Apple Pay measures and optimizes its marketing. You do not wait to be handed a question. Instead you identify the questions worth asking conceptualize the ideal frameworks to answer them and propose innovative approaches that others have yet to consider. You possess a deep understanding of the marketing and media landscape. You know how marketing mix models quantify cross-channel effectiveness using statistical and econometric techniques. You understandnhow incrementality testing ranging from geo-based experiments to causal inference methods isolates true causal lift. nnFurthermore you know how behavioral signals derived from clustering propensity modeling and sequence analysis can shape smarter audience strategies and campaign designs. What sets you apart is your ability to architect the right measurement framework before a single model is built. You excel at identifying the causal assumptions that must hold the confounders that must be controlled and the experimental conditions required to make results leverage Artificial Intelligence and Machine Learning to elevate these frameworks to unprecedented levels of rigor scale and speed. This includes building production-grade causal inference pipelines designing ML-powered experiment analyses and applying Large Language Models (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 and execute incrementality tests translating complex results into concrete actionable campaign advanced ML techniques such as segmentation propensity modeling and behavioral pattern recognition to identify customer response patterns and inform audience strategy and experiment with cross-functional teams to scope analytical problems define success metrics and deliver data-driven and maintain production-grade ML models and workflows that support ongoing marketing measurement and Generative AI and LLM-based tools to accelerate insight generation automate reporting workflows and streamline day-to-day analytical model outputs and experiment results clearly to both technical and non-technical audiences through compelling visualizations narratives and recommendations.

Hands-on experience in marketing science including building marketing mix models causal inference and incrementality experience designing and executing rigorous marketing proficiency in applying ML techniques to large-scale marketing and customer programming skills in Python and data science libraries (such as pandas NumPy scikit-learn and statsmodels).nAdvanced command of SQL for querying manipulating and analyzing massive marketing and media with Generative AI and large language models along with a comfort level in integrating AI tools into daily analytical written and verbal communication skills with the ability to tell compelling stories with data to diverse technical and non-technical stakeholders.

Experience analyzing paid media data across various channels including paid digital in-store media social and other performance marketing understanding of both awareness and performance marketing track record of actively following industry trends in marketing science and media measurement with a habit of bringing emerging methodologies and tools to the applying Generative AI directly to marketing workflows such as budget optimization automated creative analysis or campaign performance degree (M.S. or Ph.D.) in Statistics Machine Learning Econometrics Marketing Science or a related quantitative field.n