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Job Descrption

Requirements
• This is an ideal opportunity if you are looking for a six-month internship starting between April and July 2025, and you want to join an impactful company,
• You have a strong background and are passionate about image processing, machine learning, statistics, and operations research. You are very interested in various topics including deep learning, time series analysis, computer vision, and signal processing. You demonstrate experience in a least one of these areas,
• You have strong programming skills in Python, SQL, Machine Learning libraries, data visualization packages and data manipulation. Previous exposure to Git is preferred,
• You are dynamic, curious and eager to learn,
• You can design and deliver working prototypes in a fast-paced environment and then put them into production with the help of data engineers,
• You can communicate clearly in English, including with non-technical people,
• You are willing to work in R&D that will be put to use as part of a... product,
• You are willing to be an active member of the team and have a real impact on the company's success

What the job involves
• The team you will be joining: Products for Traders team,
• The Product for Traders team handles several products to help financial actors in the energy sector make the right decisions to accelerate the energy transition,
• Data scientists play a key role at Kayrros, working both on R&D and discovery topics,
• Most of their work consists in developing models using various methods based on recent scientific papers including computer vision, machine and deep learning, and signal processing.,
• They also collaborate with data engineers to build robust pipelines and work hand in hand with data analysts to analyze and visualise the results of their models,
• As part of the product team, Data Scientists are also expected to apply their models to various use cases, to build energy-related products,
• Formulate problems considering available data and project constraints,
• Explore and review existing approaches or relevant associated scientific literature,
• Design, implement and test algorithms,
• Continuously provide ideas to improve products and take part in all team discussions,
• Help to apply your models to “real-life” use cases,
• Grow a culture around remote sensing data, as well as large datasets

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