Global Data Scientist — ML & AI for EU Projects

Ayesa Digital; Brussel Hoofdstad; Hybride; EUR 55 000 - 90 000; Plein temps

Avantages offerts par ce poste

EU projects

International team

Expert support

Résumé du poste

Ayesa Digital seeks a Data Scientist to join its international team and contribute to business-driven data science initiatives across European projects. You will collect requirements, frame problems as data science hypotheses, define success metrics, and develop or deploy advanced data mining and ML solutions.

You will collaborate with UX/product teams, build robust data pipelines, develop predictive models for structured and unstructured data, and communicate insights through interpretable

Qualifications

• Knowledge of Python, R, SAS, Spark to design and implement data-driven solutions.
• Knowledge of ML and NLP (Scikit-learn, TensorFlow, PyTorch, Hugging Face) to build predictive and text-based models.
• Knowledge of programming languages (Python, R, SQL) for modelling and automation.
• Knowledge of MLOps practices (CI/CD pipelines, model registry, unit testing) to ensure reproducibility and quality in model delivery.
• Knowledge of BI tools (Tableau, SAS, SAP Analytics) to visualize outputs and insights.
• Knowledge of ETL tools (Talend, Informatica, dbt, Azure Data Factory) to prepare training datasets.
• Knowledge of data storage and query tech (SQL, NoSQL, MongoDB, Hadoop).
• Knowledge of scalable data storage solutions (data lakes, lakehouses).
• Knowledge of analytics applications such as forecasting, recommendations, anomaly detection, or sentiment analysis.
• Knowledge of AI governance principles aligned with EU AI Act requirements.
• Knowledge of AI compliance, bias monitoring, drift detection, model cards.
• Knowledge of GDPR, EU AI Act and designing compliant models.
• Knowledge of experiment design (A/B testing, cross-validation, significance testing).
• Knowledge of model deployment (containerization, APIs, serving frameworks).

Responsabilités

• Collaborate with UX and product teams to specify design requirements for the effective presentation and interpretation of model outputs and insights.
• Develop processes to monitor and analyse data accuracy.
• Identify, collect, and prepare data for analysis, collaborating with Data Analysts to ensure robust data pipelines.
• Produce data models according to specific problem statements.
• Develop and implement machine learning algorithms, statistical models, and scripts to solve business problems.
• Collaborate with Data Analysts and Architects on analytics architecture to support scalability and performance.
• Document tasks and liaise with other teams to address interdependencies.
• Develop visualizations to communicate model behaviour, insights, and performance metrics.
• Design, develop, and evaluate predictive models for structured and unstructured data.
• Elaborate processes to ensure compliant implementation of EU regulations including model cards.
• Maintain deployment and monitoring practices with governance considerations.
• Communicate insights to both technical and non-technical audiences.
• Conduct experiment design (A/B testing, cross-validation, significance testing).
• Deploy and maintain models into production using MLOps, CI/CD, registries, and ensuring reproducibility.

Connaissances

Python

R

SQL

NLP

ML

Formation

Specialty or Azure AI Engineer Associate

Outils

SAS

Spark

Scikit-learn

TensorFlow

PyTorch

Hugging Face

Tableau

SAP Analytics

Talend

Informatica

dbt

Azure Data Factory

MongoDB

Hadoop

Description du poste

Ayesa Digital seeks a Data Scientist to join its international team and contribute to business-driven data science initiatives across European projects. You will collect requirements, frame problems as data science hypotheses, define success metrics, and develop or deploy advanced data mining and ML solutions.

You will collaborate with UX/product teams, build robust data pipelines, develop predictive models for structured and unstructured data, and communicate insights through interpretable