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Description
Design and build a new generation of experimentation platform for the Ads Platform organization. Apply leading-edge technologies to enable safe and data driven launch of features that help connect Apple users and advertisers while delivering on Apple's privacy commitment through experimentation. Collaborate with stakeholders and data scientists to design experiments and statistical methods that account for the marketplace dynamics and yield reliable treatment effects. Provide expert technical guidance to engineers and scientists on statistical techniques, experiment design and data engineering. You will join and contribute to a culture that emphasizes observability and understandability, reliability, resiliency, simplicity, reusability, extensibility, scalability, velocity and productivity. We are one team, nurturing each other’s growth and supporting each other in delivering for our customers and Apple.
Minimum Qualifications
8+ years of experience in software and data science or statistics with an in-depth understanding of SQL and causal inference. Industry experience in SDLC is preferred. Analysis: Conduct rigorous, end-to-end analyses using SQL, Python, and statistical methods to uncover insights and improve treatment effect estimates. Experience with A/B testing infrastructure and methodologies and deep understanding of the assumptions of randomized control trials. Experience in marketplace experimentation is a bonus. Familiarity with causal machine learning tools and technologies. Well versed in observational causal techniques like regression, propensity score matching, Diff in Diff, regression discontinuity and instrumental variables. Design and analyze controlled experiments or counterfactual causal inference studies to estimate the incremental and long term impact of interventions. Experience in measuring advertiser value from campaigns or algorithmic changes is a huge plus. Proficiency in SQL and Pyspark or Scala to conduct analyses and build data products (pipelines and dashboards) to automate experiment reporting at scale. Lead the design, development, and maintenance of scalable and reliable data pipelines. Implement robust data quality checks, monitoring systems, and data lineage tracking. Advocate best practices for data engineering. Strategic Partnership: Work directly with stakeholders, including senior leaders, to identify, scope, and prioritise high-impact questions. Skilled at operating in a cross-functional organization. Ability to understand ambiguous and complex problems and design and execute analytical approaches and turn analysis into clear and concise takeaways that drive action. Curious business attitude with a proven ability to seek projects with a sense of ownership. Excellent communication, social and presentation skills. Desire to work in a fast-paced and challenging work environment. Mentor junior engineers and scientists on the team
Preferred Qualifications
Advanced Degree in Computer Science, Statistics, Applied Math or related field. 8+ years of industry experience building scalable applications.
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