Senior Data Scientist, Apple Ads

At Apple, we focus deeply on our customers' experience. Apple Ads brings this same approach to advertising, helping people find exactly what they're looking for and helping advertisers grow their businesses.

Our technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS Season Pass. Everything we do is designed for trust, connection, and impact: We respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes, from small app developers to global brands. Because when advertising is done right, it benefits everyone.

The Data Insights organization helps Apple Ads understand, measure, forecast, optimize, and improve the advertising ecosystem across Apple Services. We partner closely with Product, Engineering, Finance, Sales, and Leadership teams to solve complex business and product challenges using data, experimentation, statistical modeling, and machine learning.

We are hiring Data Scientists across multiple teams and areas of focus within Apple Ads. Successful candidates may be considered for a variety of opportunities depending on their experience, interests, and technical strengths. Our hiring process is designed to match candidates to the teams and problem spaces where they can have the greatest impact.

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.

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 closely with Product, Engineering, Sales, Finance, Marketplace, and Leadership teams

Communicate analytical findings and recommendations to both 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

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