Job Profile

The ideal candidate combines a strong technical background in machine learning with business curiosity. We are looking for someone who enjoys experimenting, measuring, and continuously improving, and who feels comfortable working side-by-side with product, engineering, and operations teams to ensure models deliver tangible results in the real world.

Requirements

• Experience: Proven track record as a Data Scientist, Machine Learning Engineer, or similar role in product or business environments.
• Fundamentals: Solid knowledge of statistics, supervised and unsupervised machine learning (regression, classification, decision trees, gradient boosting, etc.).
• Tech Stack:
  • Python: Proficiency in its ecosystem (pandas, NumPy, scikit-learn).
  • Frameworks: Experience with PyTorch or TensorFlow is highly desirable.
  • SQL: Strong knowledge of analytical queries and data modeling.
• Production: Experience building, evaluating, and maintaining models in real-world environments (ideally involving time series, IoT, telematics, or operational processes).
• MLOps: Familiarity with model/dataset versioning, performance monitoring, deployment, and experiment reproducibility.
• Infrastructure: Experience working with cloud providers (AWS, GCP, or Azure).
• Code Management: Proficiency in Git and GitHub.
• Soft Skills: Strong communication skills to present findings to both technical and non-technical audiences.
• Business Vision: Product-oriented mindset focused on understanding users and the real-world impact of models.

Desirable

• Industry: Previous experience in predictive maintenance, fleet management, telematics, or related sectors (logistics, transportation, manufacturing, oil & gas, etc.).
• ML Tools: Familiarity with experimentation and model tracking platforms such as MLflow, Weights & Biases, or similar.
• Data Engineering: Familiarity with ETL/ELT processes, orchestrators, and data warehouse/lake architectures.
• Methodologies: Experience working with Agile frameworks (Scrum, Kanban).
• Visualization: Data storytelling skills using Power BI, Tableau, Looker, etc.