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 Data Scientist, Proactive - San Diego, California, 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 - 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: 200224330 / Latpro-3774677 
Date posted: Feb-22-2021
State, Zip: California, 92101

Description

Data Scientist, Proactive

San Diego , California , United States

Machine Learning and AI

Summary

Posted: Feb 21, 2021

Weekly Hours: 40

Role Number: 200224330

Play a part in the next revolution in human-computer interaction. Do you get excited by driving product impact via measurement and evaluation, for products and services used by hundreds of millions of people globally? The vision for the Proactive Intelligence organization is to improve Apple platforms by better understanding, anticipating, and adapting to user behavior by using machine learning to build phenomenal predictive features that are built right into Apple platforms. You will partner closely with the Proactive Intelligence leadership team, as well as with product and engineering teams, to devise the data insights and reporting best practices that guide the development of current and new intelligent experiences across iPhone, iPad, HomePod, Mac, Watch, tv, and across dozens of locales.

Key Qualifications

  • Proficiency in data science, machine learning, and analytics, including statistical data analysis and A/B testing. Experience crafting, conducting, analyzing, and interpreting experiments and investigations.
  • Experience articulating and translating business questions and using statistical techniques to arrive at an answer using available data.
  • Capable of driving projects of varying sizes and scopes - some will take weeks and some months - and you will need to know when to dive deep.
  • Good judgment balancing art and science when visually communicating information (Tableau, Superset, ggplot, D3).
  • Strong communication skills and the ability to naturally explain difficult technical topics (especially causal topics) to everyone from data scientists to engineers to business partners and leaders.
  • Strong programming skills, including data-querying skills (SQL and/or Spark, etc.) and experience with a scripting language for data processing and development (e.g., Python, R, or Scala).
  • 5 years of relevant work experience.

Description

The Proactive Intelligence organization is looking for an experienced and highly motivated data scientist! You will partner across engineering groups building on-device intelligence, and evangelize a culture of using data to measure, understand, and improve our products and features. You have a background that fuses data science, engineering, and product thinking. You have years of practical experience building measurement, evaluation, and insights to improve products. IN THIS ROLE, YOU WILL: Research and develop evaluation methods to improve the quality of Proactive's user-facing products. Drive the generation of insights from raw, unstructured data to improve existing features and explore future directions. Develop extensive knowledge of existing metrics, advocating for changes where needed. Work closely with engineering teams to guarantee the consistency and validity of metrics across Proactive. Conduct analysis that includes data gathering and requirement specifications, processing, analysis, and report generation. Drive weekly metrics reports, and quarterly metrics presentations, with Apple's leadership teams. Tackle difficult, non-routine analysis problems, applying advanced analytical methods as needed. Partner with your peers to build and prototype analysis pipelines that provide insights at scale. Evangelize adoption of best practices and build greater awareness of common data analysis pitfalls.

Education & Experience

Advanced degree (MS or PhD preferred) in a quantitative field such as Statistics, Operational Research, Bioinformatics, Economics, Psychology, Computer Science, Sociology, Mathematics, Physics, or a similar quantitative field.



Requirements

See job description

 

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