EPRI’s Asset Analytics research focuses on leveraging data science and knowledge of T&S asset performance data (e.g. historical inspection, maintenance, testing, loading etc.) to perform analysis to better understand asset performance (e.g. power transformer rating calculation, classifying descriptive substation equipment work orders into specific codes – e.g. SF6 leaks, slow breakers, mechanism problems, analysis of historical maintenance (work management) data etc.) to address utility challenges. In this position the qualified candidate will support technical staff by applying skills asset performance analysis.
Conducts technical searches and analyzes information in support of the project team.
Conducts independent research and begins to manage small, less complex projects
Provides technical advice and counsel to other professionals within EPRI.
Assists Project/Program managers in assessing customer needs, formulating technical approaches, preparing proposals, technical publications/papers, and making presentations.
Reviews progress and evaluates results. Makes changes in methods, design or equipment where necessary.
Exercises considerable latitude in determining technical objectives of assignment.
Explore, Develop, and Document best practices for data science techniques to T&S asset performance data
Bachelor’s Degree in a technical field or equivalent experience required
Knowledge, Skills, And Abilities
4-5 years of engineering experience or comparable work/educational experience required.
Good verbal and written communication skills
Require some supervision and guidance to recognize strategic issues and build collaborative projects
Responsible for the success of individual projects
Works closely with contractors or staff to complete project research
May participate in multiple projects, requiring effective time-management
May present research results to advisors or technical staff/members
Starting to develop technical depth in 1-2 areas
Focus on projects within a program
The ideal candidate would possess the following:
Strong background in engineering or mathematics
Ability to extract, clean, and curate data stored in various formats and structures
Ability to load, manipulate and analyze data effectively
Experience in use of R and Python programming
Demonstrated ability to work with SQL databases
Develop innovative data visualization approaches
Working knowledge of probability and statistics