Summary

Posted: Apr 1, 2021

Weekly Hours: 40

Role Number:200234426

The Apple Media Products Engineering team is one of the most exciting examples of Apple's long-held passion for ...Summary

Summary

Posted: Apr 1, 2021

Weekly Hours: 40

Role Number:200234426

The Apple Media Products Engineering team is one of the most exciting examples of Apple's long-held passion for combining art and technology. These are the people who power the App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Books. And they do it on a massive scale, meeting Apple's high expectations with high performance to deliver a huge variety of entertainment in over 35 languages to more than 150 countries.

These engineers build secure, end-to-end solutions. They develop the custom software used to process all the creative work, the tools that providers use to deliver that media, all the server-side systems, and the APIs for many Apple services.

Thanks to Apple's unique integration of hardware, software, and services, engineers here partner to get behind a single unified vision. That vision always includes a deep commitment to strengthening Apple's privacy policy, one of Apple's core values. Although services are a bigger part of Apple's business than ever before, these teams remain small, nimble, and cross-functional, offering greater exposure to the array of opportunities here.

Key Qualifications

• Excellent communication, collaboration and planning skills; ability to understand and anticipate the decisions partners must make supported by data.
• Must have the ability to write code to query and transform both unstructured and structured data-acting as a mentor to your team in these areas.
• Ability to produce and communicate data insights that translate into significant business impact.
• Deep understanding of statistical theory and applications. Practical experience working with and conducting experiments on large datasets.
• Experience in advanced quantitative analysis including regression, classification, clustering, and time series analyses.
• Programming skills in Python, Java/Scala, and SQL, and comfort with analytics tools such as R, Spark, and/or Tableau. Solid understanding of Hadoop, ETL processes and distributed computing practices.
• Ability to communicate the results of analyses in a clear and effective manner with product and leadership teams to influence the overall strategy of the product.
• Prior experience analyzing search features utilizing online metrics and offline human relevance judgment is strongly preferred.

Are you driven to achieve and go above and beyond?

Our team is seeking a passionate leader to lead experimentation projects, analytics and data science. You will lead a team of data scientists responsible for designing experiments, conducting analysis and guiding improvements to our tools responsible for enabling experimentation across a diverse set of features - including recommendations, search and on-boarding funnels.

In this role you will design and evaluate experiments for algorithmic improvements, design and layout changes, marketing initiatives, increased cohort usage, growth and subscriber retention. Empower and mentor a team by ensuring that roles and responsibilities are clearly communicated, the strategic vision for the function is defined and shared, processes are established, and personal development plans are developed is a must.

You will work with engineers to scale up our reporting capabilities by automating and developing pipelines to execute and analyze KPIs on an hourly/daily basis and will engage the business intelligence team to collaborate on reporting that includes business relevant initiatives and metrics.

This position involves quantifying the impact of feature and model changes to the product. This team harnesses analytics and visualization of data to help understand how customers engage with our apps. Working with peer data science teams, you will develop standard methodologies and common datasets while analyzing usage behavior for large scale trends and patterns.

Education & Experience

Ph.D. or Masters in a quantitative field such as Statistics, Computer Science, or Applied Mathematics.

Additional Requirements