Research Scientist Jobs in Cupertino, CA

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 other’s 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. It’s 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.

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 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 understand

how incrementality testing, ranging from geo-based experiments to causal inference methods, isolates true causal lift.

Furthermore, 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 actionable.

You 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.","responsibilities":"Design and implement marketing mix models and causal inference pipelines that quantify marketing effectiveness and inform budget allocation decisions.

Build and execute incrementality tests, translating complex results into concrete, actionable campaign recommendations.

Apply advanced ML 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.

Architect and maintain production-grade ML models and workflows that support ongoing marketing measurement and optimization.

Leverage Generative AI and LLM-based tools to accelerate insight generation, automate reporting workflows, and streamline day-to-day analytical tasks.

Communicate model outputs and experiment results clearly to both technical and non-technical audiences through compelling visualizations, narratives, and recommendations.

Preferred Qualifications

Experience analyzing paid media data across various channels, including paid digital, in-store media, social, and other performance marketing platforms.

Deep understanding of both awareness and performance marketing measurement.

A track record of actively following industry trends in marketing science and media measurement, with a habit of bringing emerging methodologies and tools to the team.

Experience applying Generative AI directly to marketing workflows, such as budget optimization, automated creative analysis, or campaign performance reporting.

Advanced degree (M.S. or Ph.D.) in Statistics, Machine Learning, Econometrics, Marketing Science, or a related quantitative field.

Minimum Qualifications

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 (such as pandas, NumPy, scikit-learn, and statsmodels).

Advanced command of SQL for querying, manipulating, and analyzing massive marketing and media datasets.

Familiarity with Generative AI and large language models, along with a comfort level in integrating AI tools into daily analytical workflows.

Exceptional written and verbal communication skills, with the ability to tell compelling stories with data to diverse technical and non-technical stakeholders.

Pay & Benefits

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.