Data Scientist

🚀 #WEAREALTIA ALTIA is a multidisciplinary team focused on delivering advanced data-driven solutions that generate measurable impact and enable smarter decision-making. Working across international environments, we combine analytics, artificial intelligence, and business expertise to transform data into strategic value. Our mission is to help organizations evolve through innovation, scalable data platforms, and high-quality analytical solutions, fostering continuous learning, collaboration, and technological excellence. We are looking for a Data Scientist with solid expertise in advanced analytics, machine learning, statistical modeling, data governance, and AI compliance to join our team in high-impact international digital transformation initiatives applied to data-driven decision-making and analytical ecosystems. The role involves developing, validating, and deploying end-to-end machine learning algorithms, statistical models, and predictive scripts to address complex analytical challenges. The specialist will design and execute rigorous experimental frameworks (such as A/B testing, cross-validation, and statistical significance testing), as well as build scalable data integration, cleansing, and validation pipelines. Additionally, the candidate will focus on implementing responsible AI governance frameworks (aligned with transparency, explainability, fairness, and the EU AI Act), model risk management, drift/bias monitoring, and interactive Power BI reporting. In close collaboration with business stakeholders and technical teams, the specialist will perform data requirement analysis, model documentation (e.g., model cards), API-based data integration, and user acceptance testing (UAT). The position requires strong proficiency in Python, R, SQL, and Power BI, along with practical experience in distributed data architectures (data lakes, lakehouses, NoSQL) and automated data quality checks. ⭐ WHAT WE HAVE FOR YOU? 💪 Integration into an experienced and collaborative international team. 💣 Participation in high-impact international digital and ICT projects. 💙 Inclusive and innovation-driven work environment.

REQUIREMENTS:
Educational level &

Experience:
• EQF Level 7 (Master's degree or 5 years of higher education) + minimum 5 years of IT experience, OR
• EQF Level 6 (Bachelor's degree or 3 years of higher education) + minimum 7 years of IT experience. General & Domain

Experience:
• Minimum 7 years of specific experience in data analysis or data science.
• Minimum 2 years of experience in data management, analytics, or visualization applied to domain-specific areas (agricultural, environmental, or public sector datasets).
• Minimum 2 years of hands-on experience with visualization tools, trend and anomaly detection, and database environment comparison. English level: B2 or higher (spoken and written). Security Clearance: Must be eligible to obtain EU-27 security clearance. TECHNICAL & FUNCTIONAL

EXPERIENCE:
• End-to-end Machine Learning lifecycle (algorithm design, training, validation, deployment, and monitoring).
• Advanced analytics: forecasting, recommendation systems, anomaly detection, trend analysis, and statistical modeling.
• Experimental design, cross-validation, hypothesis testing, and model performance validation.
• End-to-end data lifecycle: collection, cleansing, transformation, validation, quality checks, visualization, and publication.
• Responsible AI governance principles: transparency, explainability, fairness, accountability, and alignment with regulatory frameworks (e.g., EU AI Act).
• Data storage and querying across SQL, NoSQL, MongoDB, Hadoop, Data Lakes, and Lakehouses.
• Data access and pipeline integration via REST APIs and ETL/ELT processes.
• User Acceptance Testing (UAT) for data science and AI solutions.
• Support for data providers/users through guidance, documentation, and support workflows. TECHNOLOGIES &

SKILLS:
• Programming & Analytics: Python, R, SQL, R Studio, SQL Developer, Excel.
• Visualization & Reporting: Power BI, interactive dashboards, KPI tracking, and storytelling with data.
• Databases & Storage: Relational databases (SQL), NoSQL, MongoDB, Hadoop, Data Lakes, Lakehouses, and distributed storage design.
• Data Engineering & APIs: ETL/ELT workflows, data integration, schema evolution, and RESTful APIs.
• AI Governance & MLOps: Model risk management, drift and bias monitoring, model cards, and documentation.
• Soft

Skills:
Strong problem-framing capabilities, excellent communication for complex insights, results-oriented mindset, and ability to work autonomously and in multilingual teams. NICE TO HAVE:
• Working knowledge of French is considered an asset. This job offer has been drafted taking into account impartiality and non-discrimination based on gender, race, ideology, or any other reason, in accordance with applicable equality regulations.