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Job Title:

IoT and Predictive Data Analyst

Business Area:

Product & Client Support

Location:

Lexington, KY USA

Job ID:

141188

IoT and Predictive Data Analyst

The IoT Data Analyst will work as part of the Advanced Services team to mine data from multiple sources, interpret data and create visual models that communicate data-driven insights for Predictive based services that allow stakeholders at Lexmark to make more informed decisions.

Responsibilities:

  • Perform descriptive and diagnostic analytics for the Predictive Services program
  • Mine data from primary and secondary sources, then reorganizing said data in a format that can be easily read by business teams.
  • Use statistical tools to interpret data sets, that identify trends and patterns that could be valuable for diagnostic and predictive analytics efforts.
  • Develop standard analytics that measure a program’s performance in effort, value and cost.
  • Prepare reports for executive leadership that effectively communicate trends, patterns, and predictions using relevant data.
  • Collaborate with programmers, engineers, and organizational leaders to identify opportunities for process improvements, recommend system modifications, and align with policies for data governance.
  • Create appropriate documentation that allows stakeholders to understand the steps of the data analysis process and duplicate or replicate the analysis if necessary.

Minimum Requirements:

  • Undergraduate degree in Physics, Math, Statistics, Economics, or related fields.  
  • At least 3 or more years of related experience
  • Studies in probability theory, statistical modeling, data visualization, predictive analytics, and risk management in the context of a business environment.
  • Technical skills include knowledge of database languages such as SQL, R, or Python; spreadsheet tools including Microsoft Excel; and data visualization software such as Power Bi, Tableau or Qlik.  

Preferred Experience and Skills:

  • Experience in Service delivery process and costing methodology
  • Advanced degree in Physics, Math, Statistics, Economics, or related fields.