Description
Key Responsibilities
Collaborate closely with business stakeholders to:
Understand operational challenges and strategic objectives
Translate business needs into clear data science requirements and use cases
Communicate technical results, limitations, and recommendations in accessible, non-technical terms
Design, develop, and deploy machine learning models in production environments, including:
Feature engineering, model selection, and hyperparameter tuning
Training, validation, and performance evaluation
Deployment support, monitoring, and iterative model improvement
Take ownership of the end-to-end ML lifecycle, from problem scoping to post-deployment support.
Work with structured and semi-structured data from diverse enterprise systems (ERP, MES, IoT, etc.) to build robust predictive and analytical solutions.
Develop interactive dashboards and analytical views using QlikView and Qlik Sense to visualize insights and support business decision-making.
Partner with data engineers, IT teams, and product managers to ensure scalable, maintainable, and reliable solutions.
Ensure all solutions meet industrial standards for performance, explainability, reliability, and maintainability.
Participate in client missions across Europe (short- and medium-term assignments).