Reliability Engineer

Job Location US-NC-Seaboard
ID
2021-5726
# of Openings
1
Category
Engineering
Type
Direct Hire

Overview

The Reliability Engineer is an integral part of our maintenance team focused on predictive and preventive measures for the mill. Our employees operate in a culture that values safety first and rewards hard work. We recognize and support our team culture and focus on growing our team by promoting from within – many of our employees have built their careers with us.

Responsibilities

What you will do:

  • Consult managers, area coordinators, engineers, and other stakeholders to define the scope and objective of data projects
  • Translate concepts and ideas into clearly defined quantitative models and process optimization objectives that capture both business and user requirements
  • Work with IT, engineers, and applications developers to explore, clean, and manipulate data to prepare data sets for machine learning / statistical modeling
  • Assist in the design, implementation, and evaluation of data models, including the use of multivariate techniques
  • Communicate results of data-driven modeling projects both in terms of development status and ongoing operational findings and actions
  • Provide input on user interfaces for models that are easily accessible to users from varying backgrounds (plant operators, engineers, IT professionals, etc.)
  • Establish processes that allow others to successfully adopt and maintain model applications with minimal oversight, and act as a liaison between data applications development and operational departments as well as the executive
  • Diagnose existing models in MPC controllers in the plant and provide decision support for MPC implementation and instrumentation
  • Act as an in-house strategic translator by providing independent verification and thoughtful critique of third party data analysis and data products

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Qualifications

Qualifications you should have:

  • Must be self-driven and motivated to learn new data science skills with minimal supervision
  • Proficient in written and verbal communication skills
  • Willingness to adapt in order to thrive in a collaborative environment
  • Demonstrated quantitative analysis skills and proficiency in working with applications developers, IT, and other technical domains
  • Experience in communicating and presenting data and technical concepts to audiences with varying backgrounds
  • Degree in math/statistics or engineering

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