DID S.r.l. ricerca un Data Scientist – Advanced per un incarico presso un'Istituzione Europea (unità di ricerca su filiere sostenibili e bioeconomia UE). Di seguito il testo integrale dell'opportunità.
JOB OPPORTUNITY · EU INSTITUTIONS — Data Scientist – Advanced
EU Bioeconomy · Agricultural Data · Multiscale Relational Database
CLIENT: European Institution – research directorate (Sustainable Resources / Bioeconomy)
PROFILE: Data Scientist – Advanced level
WORK MODE: Far-site (remote), occasional on-site presence in Ispra (VA), Italy, on request
CONTRACT: Time & Means, specific contract (may be executed in phases)
EXPERIENCE: Minimum 10 years of IT professional experience
EDUCATION: Master's degree (EQF Level 7) or 5 years of higher education
LANGUAGE: English C1 or higher (spoken and written)
MAX RATE: 300-350 € / day
BACKGROUND & MANDATE
DID S.r.l. is looking for an Advanced Data Scientist for a far-site assignment with a European Institution, within a research unit working on sustainable supply chains and the EU Bioeconomy. The consultant will take charge of the selection, collection, verification and integration of data into a multiscale (EU, Member State, regional) relational database representing the EU Bioeconomy, following a 'societal metabolism' approach to whole social-ecological systems. The role combines data engineering, quantitative analysis, AI-assisted data exploration and science-for-policy communication, in a multicultural and multilingual environment where accuracy, discretion and reproducibility are essential.
MAIN TASKS
- Database architecture: design and evolve the multiscale relational database of the EU Bioeconomy, including interlinkages between European production and consumption systems
- - Agricultural data analysis: identify, collect and prepare EU, international, national, regional and local statistical datasets on the agricultural sector (incl. CAPRI outputs, trade data, time series), with data quality and consistency checks
- - Data integration: integrate agricultural data into the database, ensuring interoperability with datasets from other sectors
- - AI-enabled data access: improve the data exploration interface for scientists and stakeholders, including agentic AI tools to query the database in natural language
- - Scenarios & reporting: contribute to forward-looking scenarios on the EU Bioeconomy and global megatrends; develop and update the "Bioeconomy Bulletin" at Member State level
- - Visualisation & communication: statistical and quantitative analysis, charts, infographics, layouts and presentations for science-for-policy products
- - Stakeholder engagement: take part in workshops and policy events; work with industry, academia and SMEs to collect data, define metrics and deploy data-mining solutions
- - Documentation: technical documentation, training and workshop material, contributions to scientific publications
MANDATORY REQUIREMENTS (declared in the CV and verified during evaluation; offers not meeting these minimum requirements are rejected)
- MuSIASEM (Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism) applied to quantitative assessments: 36 months
- - Python programming: 12 months
- - Web programming: HTML5, CSS3, SASS, JavaScript / ECMAScript 6 with D3.js: 12 months
- - At least one Adobe suite component (InDesign, Acrobat, Illustrator): 6 months
- Assessed through the technical questionnaire (deep knowledge required): European agricultural sector datasets (Eurostat, FAO, CAPRI model outputs, trade data); data analysis & ETL pipelines; data warehouse architecture and dimensional modelling; Power BI and DAX programming language.
TECHNICAL PROFILE
- excellent knowledge of the MuSIASEM approach and of Life Cycle Analysis (LCA) tools and approaches
- - robust experience in cleaning, managing and structuring large datasets; relational databases and structured reference / terminology collections
- - AI technologies for interfacing with databases, data integrity and interoperability checks, iterative incremental model runs
- - statistical analysis and validation methods (hypothesis testing, cross-validation)
- - version control, containerisation and testing practices (Git, GitHub / GitLab) to guarantee reproducible, high-quality code
SOFT SKILLS
- environmental specialist with significant experience in environmental data analysis and mathematical modelling for environmental assessment
- - ability to present complex ideas clearly to any audience and to facilitate multi-stakeholder events
- - problem framing, hypothesis building and solution design; strong commitment to accuracy and integrity
- - team player and autonomous, results-oriented; comfortable in multilingual meetings
WORKING CONDITIONS
- far-site delivery; on-site presence in Ispra only when requested, with at least 14 calendar days' written notice
- - working days between 7:00 and 20:00, with guaranteed availability 9:30-12:00 and 15:00-16:30 (16:00 on Fridays), local time
- - no service on the official holidays of the Institution's Ispra site
- - no security clearance and no certifications required; signature of the Institution's Ethics reminder
SELECTION PROCESS
- CV in English, clearly showing the months of experience for each mandatory skill.
- 2. Technical questionnaire: 8 open questions (MuSIASEM, Python, web, Adobe, agricultural datasets, ETL, data warehouse & AI, Power BI/DAX). Minimum score 70% overall. Answers must be written personally: the use of AI tools or any external assistance is strictly forbidden and leads to rejection.
- 3. Possible remote live interview (Teams / Webex, at least 3 working days' notice). Attendance is mandatory and no external help is allowed.
DID S.r.l. · hr@did.srl · jobs.did.srl