Apple

Data Scientist - Streaming Media


This job is now closed

PayCompetitive
LocationSanta Clara/California
Employment typeOther
  • Job Description

      Req#: 200477657

      Summary

      Do you want to make an impact on how millions of people around the world experience Streaming content using their Apple devices? If you love statistics, machine learning, data analysis and having a global impact then look no further. Imagine what you could do here! The Streaming Media team within Audio and Media Technology Group provides insights that drive decision-making for our engineering and product partners and help develop novel machine learning applications to create the best streaming experience for our users. You'll be working daily with engineers, data scientists, cross functional partners, and leadership across Apple to help drive innovation and improve our product.

      Key Qualifications

      • Data-querying skills (SQL and/or Spark, Pandas etc.) along with experience with a scripting language for data processing and development (e.g., Python, R, or Scala)
      • Experience with machine learning frameworks such as Scikit Learn, TensorFlow, and Keras and understanding of Machine Learning algorithms, including regression, clustering, classification, and neural networks.
      • Expertise with statistical data analysis, multivariate analysis AB testing & sampling methods
      • Strong communication and collaboration skills
      • Self-motivated and curious with demonstrated critical thinking capabilities and an ability to work with ambiguity.

      Description

      In this role you will, experience articulating and translating questions and using statistical techniques to arrive at an answer using available data. Develop tools and methods to improve the data analysis, visualization, and processing. Help innovate, design & implement machine learning based solutions to improve user experience during content streaming. Collaborate with a team of engineers and cross-functional product leaders to bring analytics rigor and statistical methods to ensure great product quality and amazing user experience.

      Education & Experience

      BS or MS in a quantitative discipline (Statistics, Operational Research, Bioinformatics, Economics, Computer Science, Sociology, Mathematics, Physics, or similar quantitative field) or equivalent practical experience.

      Additional Requirements

      • Nice to have but not required.
      • - Software development experience in C, C++, ObjC or Swift
      • - Experience with Splunk and Tableau

      Pay & Benefits

      • At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $105,500 and $196,500 annualized, and your base pay will depend on your skills, qualifications, experience, and location.

        Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.

        Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
  • About the company

      Work at Apple! Join a team and inspire the work. Discover how you can make an impact: See our areas of work, worldwide locations, and opportunities for students.

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