Our client, a renowned European Institution in Seville, is the European Union’s science hub.
The organisation plays a vital role in supporting EU policymaking through rigorous, high-quality research across key areas that directly impact the lives of all Europeans, from AI to territorial transformation, clean industry, and fiscal policy.
We are seeking a skilled Data Scientist with advanced R developer skills, who will play a key role in a geographic information system project.
This initiative focuses on analyzing decarbonization data for energy-intensive industries, supporting corporations in the credibility of their transition plans for a more sustainable economy.
Contract type offer:
~ Freelancer
Develop a semi-automated process to scale up the extraction from an increasing number of PDFs climate reports over time (leveraging AI LMM and machine learning)
Conduct data analysis to complement the dataset with publicly available data (e.g. press released) or private databases
Explore and propose options to scale up the database from an EU-centric approach to a Global approach
Propose and implement IT solution to connect the database to the existing preliminary version of the analytical tool
Perform analysis at corporate, sectoral, or geographical level (local, regional, country) to identify trends, patterns, and statistical insights (using data analysis tools and techniques)
with GIS, Tableau, or Power BI)
Based on the analysis performed, propose new features for improving the GIS tool and implement them
Update the underlying data sources included in the GIS tool
Experience with building data pipelines to extract, clean and structure data from diverse sources (e.g. PDFs, databases, APIs)
Experience with database management and design (e.g. relational databases, NoSQL databases)
Strong programming skills in languages such as R, Python are required
Ability to work with large datasets and perform data quality checks
Experience with data visualisation and communication of complex data insights to non-technical stakeholders
Knowledge of machine learning and AI techniques, particularly in natural language processing (NLP) and text analysis
Familiarity with geospatial analysis and mapping tools such as GIS, Tableau, or Power BI
Experience or understanding of climate-related data
Familiarity with cloud-based data platforms and services (e.g. AWS, Google Cloud, Azure)
~ Bachelor's or Master's degree in a relevant field such as Computer Science, Data Science.