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Sr. Data Scientist - Applied Machine Learning - Apple


Santa Clara Valley, California
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Job Details

Apple's Applied Machine Learning team has built systems for a number of large-scale data science applications. We work on many high-impact projects that serve various Apple lines of business. We use the latest in open source technology and as committers on some of these projects, we are pushing the envelope. Working with multiple lines of business, we manage many streams of Apple-scale data.

Join Apple’s Applied Machine Learning Team as a Data Scientist. We are looking for a candidate who can leverage/develop innovative machine learning and data mining technologies, for solving novel and diverse sets of problems. Candidate should have a strong background and experience in machine learning and information retrieval.

Must have experience managing end-to-end machine learning pipeline from data exploration, feature engineering, model building, performance evaluation, and online testing with TB to Peta bytes size data sets.


The Data Scientist will deal with large-scale data set with intensive hand-on code development. In addition, this role will be responsible for the following:

Collect, process and cleanse raw data from a wide variety of sources.

Transform and convert unstructured data set into structured data products.

Identify, generate, and select modeling features from various data set.

Train and build machine learning models to meet business goals.

Innovate new machine learning techniques to address business needs.

Analyze and evaluate performance results from model execution.PhD in Computer Science, Machine Learning or Statistics desired.


Key Qualifications

  • Experience communicating with diverse teams including data scientists, engineers, product managers, and executive management.
  • Proven track record of delivering high quality analytics insights and solutions.
  • Deep understanding, analysis, and mining of large corpora of structured and semi-structured data.
  • Knowledge and experience managing and analyzing global data.
  • Strong experience with Big Data (min 2 years of hands-on experience working on TB to PB scale datasets)
  • Dataset experience in document, graph, log data, and semi-structured data
  • Strength in Machine Learning, Statistical Modeling, Data Mining, Pattern Recognition, Information Retrieval, Natural Language Processing, or Search Ranking
  • Experience innovating and implementing novel ML techniques
  • Experience using all these ML techniques: clustering, regression, classification, graphical models, mixture models, topic models, and matrix factorization
  • Self driven individual who can take a high-level problem and see it to completion
  • Knowledge of distributed computing solutions and ability to leverage them towards gaining faster insights from data.
  • Excellent communication and team promotion skills.


PhD in Computer Science, Machine Learning or Statistics desired.