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Role Summary: The incumbent actively participates in the development of web-based wind turbine engineering applications, implements/validates methods/processes for analysis of the wind resource and execution of site-specific mechanical loads calculations, optimization of the electrical yield, and for automation of the respective processes. She/he will be responsible for software development projects, automation of wind turbine simulation and pre-/postprocessing, software testing, and validation of results.
Essential Responsibilities: As an integral part of GE, this critical role helps us to add value to wind turbine solutions for the customer by providing the application engineering team with software tools encompassing the latest understanding of wind resource assessment (WRA), mechanical loads analysis (MLA) and wind turbine operation.
In this role, you will:
Develop solutions to increase customer value and enable digital wind farm optimization
Within a SCRUM team, work independently on software development tasks with a strong focus on quality and software design
Challenge the other members of the development team on questions of software design and quality
Independently develop automated software tests
Write developer documentation
Understand and challenge current application engineering processes from raw measurement to site specific component checks and report generation
Bachelor’s Degree in computer science, computer engineering, information systems, mechanical engineering, mathematics, or comparable education from an accredited college or university
Proven project experience in developing scientific/engineering applications, in building responsive, interactive frontend applications, or in data science, using AGILE processes.
Strong proficiency in English, with multi-lingual capacity
Demonstrated interest in Digital technologies
Comfortable with software build tools (e.g. Maven, Gradle), version control (Git), build/test automation (e.g. TeamCity, Bamboo, Jenkins) and common software design patterns
Experience with Python (Numpy, Panda) and R (dplyr, ggplot) for scientific or engineering applications
Project experience with Java; knowledge of Java frameworks and libraries
Good background in Statistics
Experience in machine learning, surrogate modelling, design of experiment, optimization (Genetic algorithm, multi-objective, gradient-based) or uncertainty quantification (monte-carlo) are a plus.
Familiarity with mechanical load analysis or wind resource assessment are a plus
Strong written, oral, & presentation skills
Ability and willingness to accept challenges outside of technical expertise / comfort zone
Self Motivated, Team player, with Demonstrated Creativity and Fulfillment
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