
Data Scientist, Apple Pay
Cupertino, CAFull-timeSeen 4w agoSeen in employer's feed 1 day ago
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Job overview
Apple seeks an experienced Data Scientist to reimagine how Apple Pay measures and optimizes marketing. The role develops measurement frameworks, evaluates causal assumptions and confounders, and uses AI/ML to build rigorous, scalable analysis. The work spans marketing mix models, experiments, causal inference, audience strategies, and campaign design. The posting also describes applying generative AI to insight generation and communication.
Skills & qualifications
Skills
Qualifications
Full job description
Weekly Hours: 40
Role Number: 200683123-0836
Summary
Apple is where individual imaginations gather together, committing to the 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 other's ideas stronger. That 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. It's the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you'll do more than join something — you'll add something. At Apple, extraordinary ideas have a way of becoming great products, services, and customer experiences very quickly.
Description
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 don't wait to be handed a question; you identify the questions worth asking, conceptualize the right framework to answer them, and propose approaches that others haven't 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 wouldn't 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.
Minimum Qualifications
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• Hands-on experience in marketing science, including building marketing mix models, causal inference, and incrementally measurement
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• Experience designing and executing marketing experiments
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• Proficiency in applying ML techniques to marketing and customer datasets
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• Strong proficiency in Python and data science libraries (pandas, NumPy, scikit-learn, statsmodels, or equivalent)
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• Strong command of SQL for querying and analyzing large-scale marketing and media datasets
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• Familiarity with Generative AI and large language models, and comfort integrating AI tools into day-to-day analytical workflows
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• Strong written and verbal communication skills and are able to tell compelling stories with data to both technical and non-technical audiences
Preferred Qualifications
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• Experience with paid media data across channels, paid digital, in-store media, social, and other performance marketing platforms
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• Experience with awareness and performance marketing measurement
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• Actively follows industry trends in marketing science and media measurement — aware of emerging methodologies and tools and brings those perspectives into the team
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• Experience applying Generative AI to marketing workflows, including budget optimization, automated creative analysis, or campaign performance reporting
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• Advanced degree (M.S. or Ph.D.) in Statistics, Machine Learning, Econometrics, Marketing Science, or a related quantitative field
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.
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