Data Scientist
NATURE OF THE TASKS
Service provision will take place within a large international organisation, such as the
European Commission. The working environment is multicultural and multilingual, with an
emphasis on strong work ethics, diligence, and responsibility. A shared commitment to
common goals and operational effectiveness is essential, as is a high degree of discretion
when handling personal or confidential data. The selected service provider will be required to
sign the Ethics reminder and to conduct themselves accordingly during the provision of
services under the awarded specific contract.
The service provider is expected to take on data science activities in support of DG ECFIN IT
unit, according to the needs defined by the project and service managers.
DG ECFIN.R3, in partnership with other Commission services and stakeholders, manages IT
solutions both for DG ECFIN and line DGs, enabling the successful implementation of
ECFIN’s core business activities. In close collaboration with other Commission services and
its customers, DG ECFIN.R3 builds and operates solutions in the area of the economic and
financial domain. Amongst the solutions provided are IT systems related to fiscal
surveillance, the European Semester and the Recovery and Resilience Facility.
The tasks that the service provider will be expected to perform include any or all of the
following:
• Collaborate with stakeholders to collect requirements, frame business problems as
data science hypotheses, define success metrics, and develop or deploy advanced data
mining and machine learning solutions.
• Develop processes to monitor and analyse data accuracy.
• Identify, collect and prepare data for analysis, collaborating with Data Analysts to
ensure robust production-grade data pipelines, with a focus on feature engineering and
data readiness for modelling.
• Produce data models according to specific problem statements.
• Develop and implement machine learning algorithms, statistical models and scripts to
solve specific business problems.
Collaborate with Data Analysts and Architects on the design of the analytics
architecture to ensure it supports the scalability and performance requirements of data
science models.
• Write the different documentation associated with the tasks and liaise with other
teams as necessary to address cross-system interdependencies.
• Develop visualisations to communicate model behaviour, key insights and
performance metrics, and collaborate with Data Analysts on integrated dashboard
reporting.
• Design, develop and evaluate predictive models capable of handling both structured
and unstructured data, including model selection, training and hyperparameter tuning.
• Elaborate processes to ensure the compliant implementation of regulatory
frameworks, including model risk management, monitoring for drift and bias, and
comprehensive documentation.
• Ensure that model development, deployment and monitoring practices adhere to all
relevant regulatory frameworks and internal governance policies.
• Communicate model insights, limitations and behaviour effectively to both technical
and non-technical audiences, and create interpretable outputs and documentation.
• Conduct rigorous experiment design, employ cross-validation techniques, and
perform statistical significance testing to validate findings and model performance.
The following minimum mandatory requirements apply and shall be verified through
evidence provided in the CV:
• 10 years of expertise in using Python (level 5/5 Advanced)
• 10 years of expertise in using SQL (level 5/5 Advanced)
• 10 years of expertise in using Oracle or PostgreSQL (level 5/5 Advanced)
• 5 years of expertise in using Python NumPy (level 5/5 Advanced)
• 5 years of expertise in using Python SciPy (level 5/5 Advanced)
• 5 years of expertise in using Python Pandas (level 5/5 Advanced)
• 5 years of expertise in using Python Matplotlib (level 5/5 Advanced)
• 5 years of expertise in using NodeJs (level 5/5 Advanced)
• 5 years knowledge of Confluence, Bamboo Bitbucket (level 5/5 Advanced)
• 3 years of expertise in using Airflow (level 3/5 Good)
• 2 years of expertise in using SDMX (level 3/5 Good)
• 6 months of expertise in using Amazon Q/Kiro (level 3/5 Good)
• 1 year of expertise in using R Language (level 3/5 Good)
2.1.2 Business requirements
The candidate shall demonstrate the following minimum requirements, verified through
evidence provided in the CV:
• 5 years of expertise in economic forecasting (level 4/5 Advanced)
• 5 years of expertise in economic modelling (level 3/5 Good)
