261 jobs for "Lead Data Scientist"

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Data Scientist

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Director, Data Science

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Apple

Data Scientist, Apple Pay

Cupertino, CA$184,700 – $277,600Posted 23 days ago

Apply on company site View full job

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.","responsibilities":"• Design and implement marketing mix models and causal inference pipelines that quantify marketing effectiveness and inform budget allocation decisions
• Build and execute incrementally tests and translate results into concrete campaign recommendations
• Apply 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
• Build 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 visualizations, narratives, and recommendations

Preferred Qualifications
• Experience with paid media data across channels, paid digital, in-store media, social, and other performance marketing platforms
• Experience with awareness and performance marketing measurement
• Actively follows industry trends in marketing science and media measurement - aware of emerging methodologies and tools and brings those perspectives into the team
• Experience applying Generative AI to marketing workflows, including 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 incrementally measurement
• Experience designing and executing marketing experiments
• Proficiency in applying ML techniques to marketing and customer datasets
• Strong proficiency in Python and data science libraries (pandas, NumPy, scikit-learn, 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 day-to-day analytical workflows
• Strong written and verbal communication skills and are able to tell compelling stories with data to both technical and non-technical audiences

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 $184,700 and $277,600, 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.

About Apple

Working at Apple means doing more than you ever thought possible and having more impact than you ever imagined.

Size: 10,000+ employees
Industry: Technology

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