Machine Learning Engineer (App Store), Apple Media Products Data Science


Job Overview

Key Qualifications

  • 3+ years of experience in a Machine Learning Engineer or Applied Scientist role, preferably for an internet technology company.
  • Familiarity with broad range of Machine Learning techniques and relevant statistical packages to engineer Machine Learning solutions end-to-end.
  • Strong proficiency with SQL-based languages, Python, Spark, and additional large-scale data / Hadoop-ecosystem tools. Working proficiency with Git.
  • Experience in contributing to production code bases. Ability to rapidly prototype algorithmic ideas in notebook environments and translate them into production code.
  • Curious business attitude with an ability to condense complex concepts and models into clear and concise takeaways that drive action
  • Excellent communication, social and presentation skills with meticulous attention to detail
  • Prior experience in the user acquisition, advertisement, and media space is preferred, but not required.
  • Description

    Collaborate with App Store stakeholders and partners to design Machine Learning models that help us better understand, acquire, and advertise to our App Store users.Engineer end-to-end Machine Learning products which provide App Store partners with a granular understanding of customer preferences and user value drivers, including scalable solutions for customer acquisition and targeting. Support engineering, business, and marketing teams at Apple in optimizing all customer touch points by detecting usage patterns with data-driven / machine-learned methods and translating them into impactful solutions. Dive deep into large-scale data sources to uncover opportunities for Machine Learning automation, predictive methods, and quantitative modeling across the App Store. Partner with other Apple organizations on data engineering, data governance, evangelizing Machine Learning, and democratizing data. Increase internal adoption of ML and AI products. Your creative solving skills will be utilized daily.

    Education & Experience

    Minimum of a Bachelors degree in Computer Science, Statistics, Mathematics, Engineering, or related field. Ideally, Masters or PhD in related field.

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