We are looking for a Data Scientist Intern to join our technical team and contribute to the development of our in-building waste intelligence platform. Our solution combines IoT sensors, mobile applications, and cloud-based analytics to help organizations measure, report, and reduce their waste footprint.

As a Data Scientist Intern, you will:

• Work with live sensor and image data to generate insights that drive sustainability decisions.

• Contribute to building and improving our AWS-based data infrastructure (Glue, Athena, QuickSight, SageMaker).

• Build models to estimate waste data at a large scope from a sample of monitored waste stations

• Evaluate machine learning models to predict the impact of waste management initiatives.

• Develop analytics to:

  • Track waste generation at the bin/floor/building level.

  • Detect anomalies and inconsistencies in waste measures.

  • Standardize data across customers to enable benchmarking.

• Create compelling data visualizations and dashboards to support customer decision-making.

This internship is an opportunity to apply data science and machine learning skills to a real-world sustainability challenge and have a measurable impact on how organizations manage their waste.

We are looking for candidates who bring a mix of technical skills and motivation to make a difference:

• Proficiency in Python and PySpark for data analysis and experience with ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch).

• Familiarity with cloud data analytics (AWS S3, Glue, Athena, QuickSight, SageMaker).

• Experience with data visualization tools and libraries.

• Comfortable working in an Agile/SCRUM environment.

• Strong interest in sustainability and environmental impact.

• Personal values aligned with our team culture: trust, transparency, respect, and kindness.

The selection process includes an initial screening, followed by a general interview with our CTO (conducted in French). Shortlisted candidates will then proceed to a technical interview with members of the R&D team.