Senior Data Scientist, Marketing Analytics
Apple
Marketing & Communications, Data Science
Cupertino, CA, USA
Posted on May 14, 2026
At Apple, extraordinary products begin with a deep understanding of the people who use them. The Product Marketing Analytics team sits at the intersection of data science and marketing strategy, transforming customer data into communications that resonate with Apple product owners worldwide. As a Senior Data Scientist, you will partner with Marketing Communications and cross-functional teams to develop insights, dashboards, and predictive models that enable more relevant and meaningful customer engagement. You will proactively identify opportunities, apply advanced analytical and AI-driven approaches, and deliver end-to-end solutions that shape how millions of people experience Apple products.
As a Senior Data Scientist on the Product Marketing Analytics team, you will generate customer insights and build predictive models to support personalized, data-driven marketing communications. You will identify business problems, define analytical frameworks, and translate complex data into clear visualizations and actionable recommendations that inform marketing strategy, product adoption, and customer engagement. You will lead analytical initiatives end-to-end—from scoping and data preparation to modeling and delivery—while partnering with Engineering and Machine Learning teams to build scalable solutions. You will also leverage modern AI and LLM-based tooling to accelerate workflows and enhance analytical output.
- Proactively identify business problems and analyze customer behavior to inform strategies for product purchase, upgrades, and cross-product expansion
- Translate analytical findings into clear visualizations and actionable recommendations for Marketing Communications and cross-functional partners
- Design, build, and maintain Tableau dashboards to track the impact of product launches and marketing activities on a regular cadence
- Develop and apply machine learning models (e.g., classification, regression, ensemble methods) to optimize marketing strategies and personalization efforts
- Partner with Engineering and Machine Learning teams to develop scalable data pipelines and production-ready modeling solutions
- Leverage LLMs and agentic AI workflows to streamline analysis, automate repetitive tasks, and accelerate insight generation, visualization, and modeling
- Analyze market investments, including pricing, marketing mix, attribution, channel performance, and partner program effectiveness
- Lead data preparation, integration, and quality assurance to ensure robust and reliable modeling outputs across the project lifecycle
- Graduate degree in Business (quantitative focus), Statistics, Data Mining, Machine Learning, Analytics, Econometrics, Mathematics, Operations Research, Industrial Engineering, or a related field with 4+ years of experience OR Bachelor's with 6 years of relevant experience.
- Strong foundation in machine learning methods, including classification, regression, clustering, and ensemble techniques
- Proficiency in Python or Spark, with experience developing production-level analytical solutions
- Advanced SQL skills, including query optimization and data modeling in Snowflake
- Experience building and maintaining data visualization dashboards using Tableau or other visualization tools
- Strong business acumen with the ability to connect analytical insights to strategic decision-making
- Experience with advanced marketing analytics techniques (e.g., time-series regression, marketing mix modeling, multi-touch attribution)
- Experience using LLMs and AI-assisted tooling to improve analytical productivity
- Experience presenting analytical findings and recommendations to senior leadership
- Experience managing end-to-end analytics projects with multiple competing priorities
- Experience partnering with technical and non-technical teams to translate business questions into analytical frameworks
- Experience working with incomplete or ambiguous data to deliver results in a dynamic environment