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Description
As a Data Scientist within Data Insights, you will work on high-impact problems that influence product strategy, business performance, advertiser outcomes, and marketplace health across Apple's advertising platforms. Depending on your area of focus, you may contribute to one or more of the following domains: - Product and Marketplace Insights: Define measurement frameworks, design experiments, evaluate product and advertiser outcomes, and identify marketplace opportunities that influence product strategy and decision-making. - Business Insights: Own key business metrics, identify drivers of business performance, and translate analytical findings into actionable recommendations for leadership. Build scalable analytical frameworks and automation solutions that improve decision-making across the advertising ecosystem. - Predictive Modeling, Forecasting & Optimization: Develop forecasting, machine learning, and optimization models that improve business performance and operational decision-making. Design robust evaluation frameworks and translate model outputs into scalable business impact. - Advertiser GTM Research - Quantitative Research & Econometrics: Apply statistical, econometric, optimization, and causal inference techniques to better understand marketplace behavior, advertising effectiveness, and incrementality in support of strategic decision-making. We hire across multiple levels and specialties within the Data Insights organization. Candidates may be considered for different teams and opportunities based on experience, interests, and business needs. Our goal is to match exceptional talent to the problems where they can create the greatest impact.
Minimum Qualifications
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 an 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
Preferred Qualifications
Masters or PhD in Statistics, Economics, Mathematics, Computer Science, Engineering, Data Science, or a related quantitative discipline and experience in one or more of the following areas: 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 Forecasting and time series analysis, including revenue, supply, or demand forecasting Building data products, analytical frameworks, or decision-support systems Experience partnering with Product, Engineering, Sales, Finance, or executive leadership teams to drive business outcomes
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