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 Data Scientist - Experimentation, Apple Media Products - Seattle, Washington, United States

   
Job information
Posted by: Apple 
Hiring entity type: Retail 
Work authorization: Not Specified for United States
Position type: Direct Hire, Full-Time 
Compensation: ******
Benefits: See below
Relocation: Not specified 
Position functions: Computers - Programming Languages
Computers - Platforms
Computers - Networks
Computers - Software Engineer
 
Travel: Unspecified 
Accept candidates: from anywhere 
Languages: English - Fluent
 
Minimum education: See below 
Minimum years experience: See below 
Resumes accepted in: English
Cover letter: No cover letter requested
Job code: 200284641 / Latpro-3821211 
Date posted: Sep-03-2021
State, Zip: Washington, 98199

Description

Data Scientist - Experimentation, Apple Media Products

Seattle , Washington , United States

Software and Services

Summary

Posted: Sep 3, 2021

Weekly Hours: 40

Role Number: 200284641

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 Apple's 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.

Key Qualifications

  • Extensive background in statistical methods and data mining
  • Excellent applied statistics skills, such as hypothesis testing, experimental design, sample size determination and non-parametric statistics
  • Experience with big data systems and distributed computing, such as Hadoop.
  • Experience with common data science toolkits, such as R, pandas, dplyr, NumPy,, etc
  • Experience with data visualization tools, such as GGplot, etc.
  • Proficiency in using query languages such as SQL, Hive and SparkSQL
  • Experience with programming languages such as Scala, Spark or Python
  • Great communication skills and ability to explain findings in layman terms
  • Keep up-to-date with latest technology trends
  • Communicate results and ideas to key decision makers
  • Able to understand various data structures and common methods in data transformation

Description

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.

Education & Experience

Master's Degree in Computer Science, Statistics, Applied Math or related field 3-5+ years' practical experience with ETL, data processing, database programming and data analytics



Requirements

See job description

 

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