Data Scientist

Apple • San Diego, CA

4d

About The Position

The Data Scientist will work on designing, developing, and deploying machine
learning–driven marketing measurement and optimization models to inform
strategic and tactical marketing investment decisions. The role focuses on
building Marketing (Media) Mix Models, budget allocation and optimization
frameworks across sub-channels, and predictive machine learning models to assess
channel quality and efficiency. This role collaborates closely with Marketing,
Product, and Business partners to translate business problems into scalable,
explainable, and production-ready ML solutions. The ideal candidate combines
strong expertise in machine learning, statistical modeling, causal inference,
optimization, and marketing analytics with the ability to communicate insights
clearly and drive measurable business impact in a fast-paced, cross-functional
environment.

Requirements

• PhD in Statistics, Mathematics, Economics, Operations Research, or a related quantitative field with 3+ years of relevant experience; or MS with 5+ years of experience in applied modeling and optimization roles.
• Strong hands-on experience with Marketing / Media Mix Models (MMM), including budget allocation, optimization frameworks, marginal ROI analysis, and incorporating experimentation results (e.g., geo-lift tests, A/B experiments).
• Experience modeling marketing performance at granular levels, including sub-channel dimensions such as creative, placement, audience, and brand vs. performance.
• Strong foundation in statistics, regression, time-series analysis, causal inference, and optimization, with familiarity in Bayesian MMM, hierarchical models, or probabilistic forecasting.
• Experience designing, implementing, and evaluating ML models in Python, with solid understanding of model validation techniques and performance metrics.
• Proven ability to work with large-scale, multi-source datasets, and apply quantitative methods to real-world business problems.
• Working proficiency with distributed data systems and big data tools (e.g., Hadoop, Spark).
• Strong communication, collaboration, and stakeholder influence skills, with a demonstrated track record of driving business impact through data-driven recommendations.

Nice To Haves

• Ability to translate research ideas into scalable, production-level ML/AI solutions.
• Experience in building and maintaining machine learning pipelines, including data preprocessing, model training, and deployment.
• Experience developing AI tools, frameworks, or APIs to support model deployment or LLM-based applications.
• Familiarity with generative AI techniques (e.g., diffusion models, transformer architectures)

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree