Apple Ads seeks to enrich people's lives by enabling access to content while helping publishers and developers promote and monetize their work. The Data Insights team aims to leverage vast data from user searches, app metadata, and App Store content to improve customer experience and drive discovery and productivity for app developers, all while maintaining user privacy and setting new standards for advertising technology.
Requirements
- 10+ years of data science experience with 3+ years of experience leading data science, or machine learning teams.
- 2+ years of experience in mobile advertising and performance-based advertising platforms.
- Experience in statistical analysis, machine learning models, and advanced quantitative methods with a strong focus in experiment design and causal inference. Must include experience with regression, classification, clustering, time-series analysis, and LLMs.
- Exceptional programming skills in Python and SQL. Comfort with advanced analytics and data visualization tools and libraries such as Pandas, R, Spark, and Tableau.
- Deep familiarity with commonly used Statistics and ML libraries such as ScikitLearn, SparkMLLib, SciPy, and/or StatsModels. Familiarity Causal Inference packages such as CausalImpact, DoubleML, DoWhy, and EconML is a big plus.
- Experience working with modern data engineering technologies and cloud-based data warehousing solutions. Familiarity with database modeling and data warehousing principles.
- Preferred: 4+ years of experience in mobile advertising and performance-based advertising platforms, direct work experience in ad auctions, especially keyword matching, predictions, ranking, pricing, or relevance is a big plus.
Responsibilities
- Apply best-in-class modeling and analytics techniques to enable rapid insights discovery for multiple business, cross-functional teams and senior leadership
- Lead development of all predictive models on seasonality, anomaly detection, forecasting metrics for all ad businesses. Guide end-to-end lifecycle stages from PoC development, testing, industrialization and monitoring model performance.
- Lead classification and categorization of queries, apps, and discovery of app cohorts using ML models/ LLMs. Extract contextual signals from aggregated interaction data to feed into ads marketplace design.
- Lead analysis of business metrics, their interactions, and framework design on deep-dive investigations. Monitor usage metrics, provide business-based explanations for large-scale trends and patterns.
- Lead creation of self-serve, analytics tools and data products to enable insights discovery at lightning speed and scale.
- Automate and scale existing analysis methods. Institute new approaches on modeling and analysis frameworks.
- Guide statistical analysis, model development and visualization of data to help understand how advertisers use Apple Ads for app promotion.
Other
- Must be able to guide and lead ML data scientists embedded into engineering capabilities. Seamlessly collaborate with a wide range of stakeholders including senior leadership, product managers, finance, engineering. Able to create trust.
- Have a strategic mindset with an aptitude to condense complex concepts, analysis, and models into actionable data driven solutions and strategies that will propel Apple’s digital advertising businesses.
- Bachelor's in a quantitative field, such as Engineering, Computer Science, Statistics, Applied Mathematics, Econometrics, Operations Research, Social Sciences, or equivalent professional experience.
- Preferred: Ph.D. or Masters in a quantitative field, such as Engineering, Computer Science, Statistics, Applied Mathematics, Econometrics, Operations Research, Social Sciences, or equivalent professional experience.
- Exceptional communication, collaboration, stakeholder management, and planning skills; demonstrated success building buy-in for an innovative and bold vision.
