Data scientist- F/H

This Data Science position is embedded within the Market Research Team and plays a pivotal role in developing tools and analyses that drive the day-to-day decision making. The ideal candidate will have a hands-on approach, ready to dive deep into data, build models, create visualizations, and deliver actionable insights as needed. They will thrive in a fast-paced environment and be motivated by seeing your work have an immediate impact. As such, the work will focus all aspects of creating data pipelines, implementing models, reporting, and digital tools, to generate new insights and improve the accuracy of existing analyses, as well as bring agility to the consolidation and analysis of market data. This role reports directly into the Head of Market Research. Mains missions : -Establish methodologies and best practices for the entire data lifecycle, including collection, analysis, modelling, version control, documentation, testing, and monitoring. -Work in partnership with research vertical leads helping define the support needed to evolve analysis. -Assist analysts in Market Research team with technical and market-related questions. -Work closely with domain experts to design and implement solutions that are both understandable and usable by non-technical stakeholders in Tereos. -Serve as the point of contact and collaborate with IT and commercial tools manager on all aspects related to new developments, maintenance, incidents, and all digital systems and tools. -Develop and maintain automated data pipelines for ingestion, cleaning, and transformation (ETL/ELT) from multiple sources, such as APIs, databases, Excel spreadsheets, etc. -Manage and optimize databases used by the Market Research team, ensuring its performance and scalability. -Develop and maintain dashboards in Power BI, Streamlit, Excel, and other systems. -Develop predictive and statistical models for forecasting prices, consumption, weather, trade flows, arbitrage opportunities, and other indicators. -Test, validate, and monitor models using appropriate performance metrics. -Automate analytical processes and create machine learning pipelines, from training through deployment. -Contribute to ad hoc requests and recurring activities in order to provide new insights and analyses and ensure adherence to the team’s deliverables schedule. -Act as a backup, if necessary, during market team routines and presentations.