Senior Machine Learning & Data Scientist, OS Power & Performance, CoreOS

San Diego, CA, US • Posted 4 days ago • Updated 1 day ago
Full Time
On-site
Fitment

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Job Details

Skills

  • CoreOS
  • Quantitative Analysis
  • IDEA
  • Computer Hardware
  • Analytical Skill
  • Communication
  • Product Development
  • Software Engineering
  • Data Analysis
  • Machine Learning (ML)
  • Analytics
  • Python
  • Tableau
  • Conflict Resolution
  • Problem Solving
  • Collaboration
  • Computer Science
  • Electrical Engineering
  • Applied Mathematics
  • Statistics
  • Storage
  • HDFS
  • Amazon S3
  • Apache Spark
  • Extract
  • Transform
  • Load
  • Scheduling
  • Kubernetes
  • Operating Systems

Summary

Great performance is critical to Apple's product experience. We are seeking a Senior Machine Learning & Data Scientist to help with quantitative analysis of high dimensional data to draw insights that would impact hundreds of millions of users. If the idea of developing data products to improve Apple's software & hardware performance excites you, we encourage you to apply! \\n

We're looking for a proactive & impact-driven engineer with excellent machine learning, analytical, problem solving and communication skills. In this role, you will analyze high dimensional data to derive meaningful insights and be responsible for producing metrics, models, simulations, and tools for analysis & communication of insights from large datasets. To be successful, you must have a strong foundation in statistical analysis and the ability to apply it to solving business & product-development problems, as well as a strong software engineering background with the ability to write production level code. As a member of this team, you will have the opportunity to provide meaningful insights to teams and influence decisions across Apple on a broad range of products. \n

Strong Quantitative Foundation: Education in Computer Science, Electrical Engineering, or a related quantitative field. Strong mathematical foundations, software engineering, and broad knowledge of data analysis and practical machine learning are expected.\nData Engineering and Analytics: Skilled at scalably transforming raw data into actionable insights through practical problem formulation followed by building of ETL processes (e.g. Python & Spark) and data visualizations (e.g. Tableau)\nBusiness Acumen and Problem-Solving: Ability to understand the broader business context, solve complex problems, and communicate findings effectively to stakeholders.\nAdaptability and Collaboration: Comfortable with ambiguity, eager to learn, and capable of working effectively in a collaborative environment. Strong interpersonal skills and the ability to build relationships with diverse stakeholders are essential.

M.S. or Ph.D. in Computer Science, Electrical Engineering, Applied Mathematics, Statistics, or a similar quantitative field, with strong statistical skills and intuition\nProficiency in distributed compute & storage technologies such as HDFS, S3, Iceberg, Spark, and Trino\nProficiency with designing ETL flows and automation/scheduling (e.g. Kubernetes and Airflow)\nWorking knowledge of Operating Systems\nExperience driving cross-functional projects with diverse sets of stakeholders\nSkilled at connecting data insights to the company's overall strategy and objectives.\n
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 90733111
  • Position Id: 947caa15da130d4b6bf7c935477c085f
  • Posted 4 days ago
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