Data Scientist - Experimentation, Apple Media Products at Apple (Seattle, WA)
Do you want to make impact on how decisions are made by Engineering teams? If you love statistics, data, analysis and influencing teams on how to run experiments then look no further. This team in the Apple Media Products group provides insights through data that drive decision-making for our engineering and product teams. We are looking for a Data Scientist that can derive valuable insights and help us build automated reporting tools from the data we collect on AppStore, Apple Music, Movies & TV, etc. This role will be working daily with researchers and engineers on the Search and Recommendations teams as they develop better algorithms and improve their models. This in turn improves the customer experience for Apples products. You will be helping to drive innovation and improve our product decision making process while developing new experimentation methodologies, statistical techniques, and causal-inference approaches.
Our team provides insights through data that drive decision making for our engineering and product teams. We are looking for a Data Scientist that can derive valuable insights and help us build automated reporting tools from the data we utilize within AppStore, Apple Music, TV, Podcasts and Books.
Our team designs, executes and builds tools for online experiments (A/B tests) and offline experiments (human relevance judgement) that are critical to enhancing and fine tuning our data-driven features (Search, Recommendations, etc.). Your primary focus will be on applying statistical methods, develop A/B testing procedures, and automating data pipelines to develop new KPIs. Additional expectations of this role include:
Data mining using state-of-the-art methods.
Investigate new data sources that can extend and enhance our insights.
Work with software engineering teams to enhance data collection procedures.
Processing, cleansing, and verifying the integrity of data used for analysis.
Doing ad-hoc analysis and promptly presenting results in a clear manner.
Generate reports (that can be automated) to present key insights to stakeholders across engineering and product teams.
Designing experiments that will measure and test for key performance indicators.
Creativity in formulating statistical questions to address business needs.
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