🛠 Tech Stack

💼 About This Role

You'll turn high-dimensional sensor data into actionable insights and smarter models for edge-deployed systems. You'll analyze fleet data to find patterns, trends, and outliers for operational intelligence. You'll create feedback loops with machine perception teams to improve model retraining and edge-case detection.

🎯 What You'll Do

• Analyze field deployment data to uncover trends and actionable insights.
• Develop scalable analytics pipelines for customer dashboards and reports.
• Collaborate with product and customer success teams on data science workflows.
• Identify performance gaps and drift in edge-deployed models.

📋 Requirements

• 3-5 years of experience in applied data science.
• Proficiency in Python and common data science libraries (pandas, numpy, scikit-learn).
• Experience with time-series, geospatial, or multi-sensor data in production.
• Strong analytical thinking including clustering, regression, and anomaly detection.

✨ Nice to Have

• Familiarity with ML operations (dataset versioning, model monitoring).
• Experience supporting ML systems at the edge in maritime, automotive, or aerospace domains.

🎁 Benefits & Perks

• 🌍 Global impact projects
• ⏰ Flexible working hours