Apple

AIML - Sr Data Scientist, Search Analytics, Data and ML Innovation

Seattle, WA US
USD 135k - 250k
Scala Machine Learning Spark Python R
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Description
Do you get excited by driving product impact via data and evaluation, for products and services used by hundreds of millions of people globally? The vision for the AIML Data is to improve products by using data as the voice of our customers. Within this organization the mission of the team is to inform product evolution through measurement, evaluation, and analysis of the user experience. You will partner with Search engineering teams to improve search quality and guide feature development with data, to deliver amazing search experiences across iPhone, iPad, HomePod, Mac, Watch, tv, across dozens of languages.

Research and develop evaluation methods to improve the quality of Siri’s user facing products. Work with evaluation/experimentation engineering teams to get your methodological developments translated into technologies that Siri engineering will use every day. Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed. Conduct analysis that includes data gathering and requirements specification, processing, analysis, ongoing work, and presentations. Build and prototype analysis pipelines iteratively to provide insights at scale. Develop comprehensive knowledge of Siri Search data structures and metrics, advocating for changes where needed for product development. Partner closely with Siri search engineering teams on core machine learning algorithms and systems that are part of Siri’s ability to understand and respond to requests. You should be passionate about building outstanding products. This position involves a wide variety of skills and innovation.

Experience in data science, machine learning, and analytics, including statistical data analysis and A/B testing. Experience articulating and translating business questions and using statistical techniques to arrive at an answer using available data. 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. B.S. in Machine Learning, Computer Science, Statistics, Operations Research or related areas.

Hands-on experience with online AB testing platform. Experience designing, analyzing and interpreting experiments. Hands-on experience with on-device logging and metrics development. Experience with large language models, leveraging LLM for evaluation and product improvement. Ph.D. in machine learning, computer science, statistics, operations research or related areas. 8 years of relevant work experience.

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 $135,400 and $250,600, 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.
Apple
Apple
Artificial Intelligence (AI) Consumer Electronics Hardware Mobile Devices Operating Systems Wearables

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