Senior Data Scientist, Apple Ads
- Compensation
- Not disclosed
- Location
- Austin
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data science
- Posted
Skills
Must have
- 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
Nice to have
- 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
Full description
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.
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:
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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.
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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.
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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.
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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.