Data Analyst – Internship

Cork, County Cork, Ireland
Students

Summary

Posted: 20 Sep 2018
Weekly Hours: 39
Role Number: 114283259
The Mac Systems Quality team are responsible for integrated customer focussed testing on Hardware and Software programs under development and building automated tools and infrastructure to support delivery of quality Apple products. Our Mac Systems Quality team is looking for a dynamic, analytics-minded and driven analyst to join the team. You will partner closely with Engineering and QA groups throughout the product life cycle using Big Data and Advanced analytics techniques to analyse Apple’s product data to ultimately provide better products and services to our customers. You will focus on end to end quality reporting, improved data analysis capability and speed for problem solving.

Key Qualifications

  • Ability to comprehensively understand data elements, sources and relationships
  • Expertise in managing and manipulating large data sets (Python, SciKit-learn, R, JMP, Spark or equivalents)
  • Expertise in creating ad hoc and regular visualized reporting (Python, R, Matlab, Tableau or equivalents)
  • Familiarity with Splunk, Cassandra, FoundationDB and other big data tools
  • Familiarity with Machine Learning concepts and applying ML to improve data analysis
  • Data-driven and results-oriented approach to problem solving
  • Strong query execution and optimisation skills
  • Familiarity with multiple platforms, tools, methodologies in the data management, reporting and advanced analytics space

Description

In this role you will design, test, and implement highly scalable data solutions to better analyse data collected during product development cycles Develop Machine Learning Algorithms to identify problems/ trends in our data collection Interface with engineering to develop data visualisation solutions to extend and support LiveOn Develop data driven tools to measure and visualise performance and help prove engineering assumptions

Education & Experience

BS or MS degree in Engineering, Statistics, Data Mining, Machine Learning, Analytics, Mathematics or related field/ equivalent experience

Additional Requirements