AI/ML – Data Engineer (QE Analytics)

Apple
Apple

Job Overview

Key Qualifications

  • Proven experience handling relational databases and large scale distributed systems such as Hadoop and Spark along with querying languages including SQL, Hive and SparkSQL
  • 5+ years of experience in designing and maintaining a data warehouse over a complex network of data sources.
  • Proven python coding skills to move and transform data from multiple sources to a data store/warehouse
  • Good to have statistics knowledge, such as hypothesis testing, experimental design and sample size determination
  • Excellent presentation skills, distilling complex analysis and concepts into concise business-focused takeaways for leadership and peers
  • Creativity to engineer novel features and signals, and to push beyond current tools and approaches
  • 3+ years of experience to work with and manage offshore and onshore teams on multiple projects/tasks as needed
  • Great teammate with a positive attitude, strong sense of empathy with ability to make decisions.
  • Description

    As a Data Engineer in Siri Quality Analytics team, you will diagnose and evaluate the metrics used to qualify various products, features and ML models. You will support product development, quality and ML model engineers in root cause analysis of failures by providing relevant data. You play a key part in understanding the points of failure and defining metrics that can track them. You will collaborate with the analytics team by ensuring seamless, accurate and timely flow of data from various testing platforms to a central data platform. You should have a strong intuition towards understanding various logs of information and translating it to analytical schema.We promote innovation and new technology to further improve our creative output. We are seeking an innovative and passionate person to join this amazing team, if you feel this is you, we’d love to hear from you.

    Education & Experience

    M.S or Ph.D. in Computer Science, Engineering or related fields

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