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Engineering Data Scientist, Product Design

Hybrid

Added
1 month ago
Location
Type
Full-time
Salary
Not Specified

Job Responsibilities:

Fluence is looking for an Engineering Data Scientist with experience in training advanced models of physical systems to apply their skills to our energy storage products. This position is within the Product Design group and will provide support to our Core Modelling team, which predicts the behavior of battery-based electrical energy storage ‘Cores’, and tracks performance of Fluence’s fleet of batteries. Responsibilities include:

•Export, clean and organize large sets of field data, and through analysis reveal actionable information about the performance of Fluence products, including configuration limitations, asset availability, round trip efficiency, and more.

•Develop new models of physical systems, and extend established models to new applications, and implement advanced computing techniques to improve model accuracy and performance.

•Work with electrical engineers, battery engineers, and systems engineers to evaluate the combined behavior of complex grid-scale battery energy storage systems.

•Support hardware testing, test plan development, testing strategy, and prototype evaluations.

•Communicate, document findings clearly and take ownership of data-driven design recommendations which increase Fluence’s competitive advantage.

•Collaborate within cross-functional teams (Sales, Engineering, etc.), and communicate with stakeholders to understand their requirements.

•Support development of Product Guides and other documentation related to product operation and performance, for use by customers and internal stakeholders. Support sales operations by incorporating key performance metrics into Fluence’s technical sales tools.

•Perform additional responsibilities as assigned.

Job Qualifications & Skills

  • •Master’s degree in engineering, computer science, or another quantitative field.
  • 3+ years of work experience with scientific modeling of physical systems using large data sets of electrical, chemical, or mechanical engineering data.
  • Working knowledge of Python (required), and tabular databases.
  • Knowledge of data structures, coding best practices, and key tools, such as GitHub, AWS
  • Ability to work collaboratively in remote teams.
  • Fluency in English.
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