STAGE Data Scientist - Machine learning applied to solar PV

Solar PV plants convert solar energy to electricity. While operating, a large amount of data is created in the form of time series. Example variables include electrical variables (power, current, voltage…) and environmental variables (solar radiation, wind speed, air temperature…). The electrical variables describing the behaviour of plants is directly influenced by the environmental variables. Various phenomena such as defects or faults impact the behaviour of plants provoking losses in production that reduce the profitability of the PV plants.

During the apprenticeship, the apprentice will contribute to the development and maintenance of regression and classification ML models. Example of tasks include:
• Collaborating with ML engineers in the development of high complexity ML models (several areas of expertise involved, deep neural network models)
• Conduct research that can lead to the development of ML prototypes and proof of concepts
• Documentation of new ML models
• Assess the effectiveness of data sources and data-gathering techniques and improve data collection methods
• Mine, analyse and label data from company databases to drive optimization and improvement of product development
• Collaborating with software engineers to translate ML models into production systems.
• Collaborating with product managers and other stakeholders to identify new areas of potential impact.
• Querying, analysing data, and setting up monitoring and data quality assurance (including putting in place data cleaning methods if necessary)
• Maintenance and evolution of existing ML models