Machine Health Data Analyst - 2248
Job Opportunity at Productive Resources

Posted on Sep 22    641-828-6266

Location: Waterloo, IA
Job Type: Contract
Job ID: W4142892

Job Description
Productive Resources has been providing engineering services to some of the nation’s largest and most renowned companies for almost fifteen years. Our reputation for quality, teamwork, and innovative solutions keeps our clients turning to us to meet their engineering service’s needs. Our contacts and experience combined with your technical expertise equals career possibilities for you.
This opportunity is for a Machine Health Data Analyst on site at our client. As an employee of Productive Resources, you will work on a cross-functional team focused on utilizing telematics data to deliver mission-critical solutions, and you’ll do it with cutting-edge big data technologies. You will work on developing methods to analyze data from Agricultural, Construction, and Forestry machines to enable automated solutions to deliver machine uptime to our customers. There will be a focus on telematics data mining, manipulation, analytics, and automated solution development. Our team’s entrepreneurial attitude and collaborative spirit sets us apart and will keep you impassioned, driven, and fulfilled.
  • Development, maintenance, and support of methods to automate solutions to dealers.
  • Connect, flow, store, transform, analyze, and visualize data from engines and machines.
  • Integrate with engineering subject matter experts on our team to develop automated solutions using SQL and R.
  • Develop solutions for identifying patterns or trends to troubleshoot Engine related problems, using Telematics data and/or Warranty Data.
No sponsorships are available for this opportunity.
  • 2 years’ experience with writing scripts in SQL (Standard Query Language).
  • 2 years’ working experience with R or Python.
  • Good communication skills.
  • Bachelor's degree in Physics, Mathematics, Statistics, Computer Science, Computer Engineering, Data & Analytics, Mechanical or Electrical Engineering.
  • 2 years professional experience with statistical analysis methods.
  • 1-year experience with Business Intelligence tools, Tableau, or SAS.
  • 1-year experience with data warehouses Netezza or AWS.
  • year experience with the Hadoop framework, ecosystem, and additional software packages
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