Data Scientist - (90% remote) - EU Commission

For one of our main clients based in Brussels - a European Institution , we are looking for a Senior Data Scientist with expertise in Python, R language, PowerBI, SQL to support corporate solutions in the area of agriculture.

About NRB

Joining KEYES means giving purpose to your talent.

Who are we?

Are you looking for an environment where technology is not an end in itself, but a lever to build a sustainable future?

At KEYES , we are not just looking for technical expertise; we are looking for people who share our values.

Do you want to continue your career and grow within one of Belgium’s leading IT companies?

International Organizations (IO) is a dynamic global organization that takes pride in being the trusted partner of EU Institutions.

With strong commitment to excellence and a 30-years track record of delivering high-quality solutions, we are dedicated to supporting the growth and success of our clients.

Our Mission is to help our clients keep up with the challenges of digital transformation by providing the right talent at the right time for the right job.

To this end, we are constantly looking for talented professionals who are interested in working on challenging international projects and able to deliver high-quality results within multicultural environments.

Our services include (but are not limited to) modernization of solutions, digital workspaces, cloud technologies and IT security .

Our Headquarters are in Brussels and we have active accounts and offices across Europe (i.e. Luxembourg, Amsterdam, Athens, Stockholm, Geneva).

www.keyes.eu Is this YOU?

In this context, the team has launched a ‘Data analytics’ initiative to further exploit the potential of the data value chain for the Common Agricultural Policy, by leveraging on the new data technologies and processes.

Responsibilities

• More specifically, you will be responsible for… Develop and implement machine learning algorithms, statistical models, and scripts to solve specific business problems.
• Conduct rigorous experiment design (e.g., A/B testing), employ cross-validation techniques, and perform statistical significance testing to validate findings and model performance.
• Elaborate processes to ensure the compliant implementation of regulatory frameworks (e.g., EU AI Act), including model risk management, monitoring for drift/bias, and comprehensive documentation (e.g., model cards)
• Additionally, the following tasks are to be performed: Data collection, transformation and integration : Analyse the needs and identify suitable data sources and flows.
• Organise the execution of the data collection an integration processes, verify results, propose improvements and implement them in cooperation with the IT department.
• Organise the related user acceptance tests.
• This task will generate up-to-date data collection, transformation and integration processes and tools, updated databases with integrated data, up-to-date analysis documents, process documentation and reports.
• Organise the data validation and the data quality checks, including through automated processes.
• Analyze needs and create reports, data visualisations and publications, in cooperation with the IT department.
• Organise the related user acceptance tests.
• This sub-task will generate up-to-date data validation processes, updated databases with validated data, up-to-date process documentation and reports, up-to-date reports, data visualisations and publications.
• Support data providers in the communication of data through the creation of templates, tools and guidance documents.
• Support both data providers and users at various stages of the data validation processes.
• Organise the support to users asking for access, clarification or information on data.
• This task will generate templates, tools, guidance documents and managed data helpdesk tickets.
• Collaborate in assessing the implementation of DG AGRI data policies and ensure data policies are implemented for new data collections. #TRASYS

Requirements

• The unit heavily relies on data in all phases of the policy lifecycle, including policy conception, implementation, monitoring and evaluation.
• Data are either managed through EC corporate or local IT systems or collected from external sources.
• Sound principles and structures have been put in place to ensure robust data governance.
• The role includes data management, data governance and digitalization.

Are you the perfect match?

• Master’s/Bachelor’s degree; Minimum 7 years of experience in data science, data analytics and related tasks; Data analytics-related certifications; Knowledge of data storage and query technologies (e.g., SQL, NoSQL, MongoDB, Hadoop) to extract and process data at scale.
• Knowledge of designing scalable data storage solutions (e.g., data lakes, lakehouses, distributed stores) for advanced analytics and AI workloads.
• analysis, statistical processes and quality checks across the whole data lifecycle (collection, processing, integration, transformation, visualization, publication, …).
• Expertise in acceptance tests on data-related IT solutions.

Preferred

• Expertise on visualisations, trends/anomalies detection, database environment comparisons : SQL Developer, R Studio, Excel, Power BI in relation to the agriculture sector.
• Expertise on accessing data via APIs.

Please note that the position is fully remote contingent on your being a freelancer established in the EU and EU national.

The purpose of this service contract is to provide the unit with additional expertise in analytical and operational tasks connected to data collection, transformation, integration, validation and publication.

Knowledge of advanced analytics applications

forecasting, recommendation systems, anomaly detection, or sentiment analysis for business impact. Knowledge of AI governance principles (e.g., transparency, explainability, fairness, accountability) aligned with emerging EU AI Act requirements. Expertise in developing and implementing machine learning algorithms : develop and implement machine learning algorithms, statistical models, and scripts to solve specific business problems.