Overview:

• Be an integral member of the R&D data science team focused on Electric Vehicle Charging Stations (EVCS).
• Work on predicting utilization rates and energy consumption and deploying production-ready data processing pipelines.

Main responsibilities:

• Collaborate with cross-functional teams to understand business requirements and available data sources.
• Clean, process and analyze large datasets to extract actionable insights for EVCS operations.
• Develop and implement machine learning models to predict EVCS utilization and energy consumption.
• Design, implement and maintain scalable data pipelines and ensure reliability and security of data infrastructure.
• Deploy machine learning models to production on AWS and manage CI/CD for ML workflows.
• Monitor and evaluate model performance, iterating to improve accuracy and robustness.

Required profile & soft skills:

• Motivated, creative, open-minded and a team player who takes initiative.
• Passionate about new technologies and electric mobility and eager to work in a fast-growing start-up with a flat hierarchy.

Technical toolkit (what you have or are willing to learn):

• Programming: Python (NumPy, Pandas, Scikit-learn); bonus: Spark.
• ML frameworks: XGBoost, SciPy, TensorFlow, PyTorch.
• Data viz: Matplotlib, Seaborn.
• Cloud & deployment: AWS (S3, EC2, Lambda, SageMaker, Glue..), model deployment and CI/CD for ML.
• Version control: Git. Bonus: familiarity with GIS systems.

Practical information & how to apply:

• Location: Hybrid (home/office) — Office: El Ghazela Technopark, Tunis.
• Duration: 5-6 months (offered as a 4-6 months PFE internship period).
• To apply, follow the application link: https://lnkd.in/dTKNUcXe or send your application by email to contact@deepvolt.io .
• Include your CV, a short motivation letter, and any relevant project links or GitHub repositories.