Renewable Energy Co-Op/Intern

  • Schenectady, NY, USA
  • Nov 21, 2019
Internship Aerospace engineering Astronomy Biology Computer Science Chemical engineering Engineering Health Science Life Science Mathematics Medical Sciences Chemistry Civil engineering Physics Psychology Social Science Teaching/Academics Technology Veterinary medicine


Are you Interested in Renewable Energy? Have a passion for Machine Learning and applying
it to the industrial internet of things (IIoT)?

As a co-op/intern of the Renewable Energy Data Science Program, you will contribute to the
development and deployment of modern analytic algorithms to drive operational efficiency and
increase performance of Wind Turbine Generators.

Essential Responsibilities:

GE has an installed base of more than 30,000 wind turbines around the world, that each have
operational data including 50+ sensors (temperatures, pressures, speeds, etc.) and over 1,000
virtual sensor signals with resolutions ranging from 1-second to 10-minute data that can be
combined with configuration and maintenance data to provide a large, complex data set.

p>In this role, you will be part of a cross-disciplinary team on commercially-facing development
projects. These teams typically include statisticians, data scientists, data engineers, computer
scientists, software developers, engineers, product managers, and end users, working in concert
with partners in GE business units. You will use a variety of modern analysis techniques to find
structure and insights from data and convert these insights into field actions that drive efficiency,
improve reliability, and increase performance of assets.


Basic Qualifications

  • Pursuing Master’s or PhD Degree in a "STEM" major (Science, Technology, Engineering,
    Mathematics) or MBA
  • GPA: minimum 3.0 in Major
  • Eligibility Requirements
  • Legal authorization to work in the U.S. is required. GE may agree to sponsor an individual for
    an employment visa now or in the future if there is a shortage of individuals with particular skills.

Desired Characteristics: 

  • Self-starters who thrive on change, are flexible and enthusiastic about developing their
  • Passion for renewable energy and active participation in renewable energy forums,
    coursework, and/or events
  • Some experience with statistical and analytic programming (e.g., Python, R, Spark, SQL, etc.)
  • Some experience with key statistical techniques and machine learning models (e.g., feature
    selection, supervised/unsupervised learning, regression/classification, cross-validation, clustering,
    time-series forecasting, etc.)

Experience level of the applicant we want

College / Sixth form, High School