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.  

The main goal of the Data Scientist is to contribute to the development and maintenance algorithms and models. Example of tasks include: 

• Development of Business Intelligence algorithms based on the expertise of the company (PV Operation and Asset Management) 

• Development of high complexity AI models (several areas of expertise involved, from Machine Learning to Deep Neural Network models) 

• Documentation of new algorithms and models 

• Querying, analysing data, and setting up monitoring and data quality assurance (including putting in place data cleaning methods if necessary) 

• Assessing the effectiveness of data sources and data-gathering techniques and improve data collection methods 

• Mining and analysis of 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 

• Monitoring, maintenance and evolution of existing AI models with MLFlow

Technical skills

• 5 or more years of experience as a Data Scientist

• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.

• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.

• Experience in building and maintaining data pipelines and collecting data from multiple sources and formats (ETLs), and working with data science-based services that provide an API

• Demonstrable experience with Pytorch or Tensorflow

• Expertise of python data science libraries (Pandas, Numpy, Matplotlib etc.)

• Good analytical and quantitative skills with experience of SQL and python.

• Good presentation skills

• Communication skills in English (oral and written)

• Sufficient oral French to participate in collective activities and willingness to learn

Personal skills

• Responsibility

• Ability to work both independently and cohesively in a team environment

• Highly motivated and results-driven person

• Agile startup mindset, creative thinking

• Optimisation of the use of time

• Open minded

• Critical thinker

• Ability to manage stress

• Sense of anticipation, proactivity, curiosity

• Sharing knowledge (training, peer programming, workshops, etc.)

• Willingness to learn

• Accepting failure as way to improve and succeed

The recruitment process will consist of:

• A short call (30 min) with the Digital Director or a Product Manager

• A technical interview/use case with your future tech peers

• A team meeting with your future team mates (all profiles)