Senior Data Scientist, Apple Ads

Apple • Austin, TX

1d

About The Position

Apple Ads is hiring Data Scientists within its Data Insights organization to help understand, measure, forecast, optimize, and improve advertising across Apple Services, including the App Store, Apple News, and MLS Season Pass. The organization partners with Product, Engineering, Finance, Sales, and Leadership teams to address complex business and product challenges through data, experimentation, statistical modeling, and machine learning.

The role focuses on high-impact problems that influence product strategy, business performance, advertiser outcomes, and marketplace health. Candidates may be matched to different teams and areas of focus based on their experience, interests, technical strengths, and business needs. Potential areas include product and marketplace insights; business metrics and performance; predictive modeling, forecasting, and optimization; and quantitative research and econometrics related to advertiser go-to-market research.

Data Scientists analyze large-scale datasets, design and evaluate experiments, develop models, define metrics and measurement frameworks, and turn analytical findings into recommendations. They work with technical and non-technical stakeholders, translate ambiguous business questions into structured analyses, and influence product, business, and strategic decisions. The organization values analytical rigor, experimentation, and continuous learning.

Requirements

• Bachelor's degree in Statistics, Economics, Mathematics, Computer Science, Engineering, Data Science, or a related quantitative discipline, or equivalent practical experience.
• Experience in Data Science, Analytics, Machine Learning, Quantitative Research, Business Analytics, or a related field.
• Strong SQL skills and experience working with large-scale, complex datasets.
• Strong Python programming skills and experience with common analytical libraries, including understanding of code structure, testing, reproducibility, and scalable analytical workflows.
• Strong foundation in statistics, experimentation, causal inference, and analytical problem solving.
• Experience developing statistical, machine learning, econometric, forecasting, or optimization models to solve business problems.
• Experience translating analytical findings into business recommendations.
• Ability to communicate effectively with technical and non-technical stakeholders.
• Experience operating in ambiguous, fast-moving environments.

Nice To Haves

• Master's or PhD in Statistics, Economics, Mathematics, Computer Science, Engineering, Data Science, or a related quantitative discipline.
• Deep familiarity with experiment design and quasi-experimental frameworks.
• Experience applying causal inference methodologies and deriving insights from observational data at scale.
• Experience working on real-time bidding systems, advertising technology platforms, or attribution methodologies.
• Exposure to digital advertising, marketplaces, e-commerce, media, or consumer technology business-related analysis.
• Experience with forecasting and time series analysis, including revenue, supply, or demand forecasting.
• Experience building data products, analytical frameworks, or decision-support systems.
• Experience partnering with Product, Engineering, Sales, Finance, or executive leadership teams to drive business outcomes.

Responsibilities

• Analyze large-scale datasets to identify opportunities, explain business outcomes, and influence decisions.
• Design and evaluate experiments to understand the impact of products, features, and marketplace changes.
• Develop statistical, machine learning, forecasting, optimization, or econometric models to solve business problems.
• Define metrics and measurement frameworks that improve visibility into product and business performance.
• Partner with Product, Engineering, Sales, Finance, Marketplace, and Leadership teams.
• Communicate analytical findings and recommendations to technical and non-technical audiences.
• Translate ambiguous business questions into structured analytical approaches.
• Influence product, business, and strategic decisions through data-driven insights and recommendations.
• Contribute to a culture of analytical rigor, experimentation, and continuous learning.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior