About the Role
The role involves providing technical expertise in data science and artificial intelligence to improve evaluation processes, develop analytical tools, and support decision-making through machine learning and data modeling techniques.
Responsibilities
- Support the development and implementation of data science workflows
- Design and deploy AI models for performance evaluation tasks
- Collaborate with engineers to integrate machine learning into existing systems
- Analyze large datasets to extract meaningful patterns and insights
- Improve data processing pipelines for efficiency and accuracy
- Assist in validating model outputs against real-world observations
- Document methodologies and share findings with technical teams
- Contribute to the automation of analytical processes
- Maintain up-to-date knowledge of AI advancements relevant to evaluation
- Troubleshoot data quality and model performance issues
- Work closely with domain experts to define evaluation criteria
- Support the testing of AI-driven decision support tools
- Ensure compliance with data governance standards
- Optimize algorithms for scalability and speed
- Participate in technical reviews and project planning sessions
- Develop prototypes for new analytical approaches
- Translate business requirements into technical specifications
- Enhance data visualization to aid interpretation
- Support version control and collaborative coding practices
- Contribute to continuous improvement of evaluation frameworks
- Assist in benchmarking AI solutions against industry standards
- Provide technical input for project documentation
- Engage in cross-functional coordination for data integration
- Support training initiatives for team members on AI tools
- Ensure reproducibility of analytical results
Compensation
Competitive salary and benefits package
Work Arrangement
Hybrid working model with partial remote flexibility
Team
Part of a specialized evaluation unit focused on data-driven analysis and AI integration
Project Environment
- Work takes place within a dynamic evaluation setting involving satellite data, sensor outputs, and operational performance metrics
- Projects emphasize accuracy, traceability, and integration with legacy systems
Technical Expectations
- Candidates should demonstrate hands-on experience with real-world datasets
- Practical knowledge of model deployment and monitoring is essential
Available for qualified non-EU candidates
