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Build AI-Powered Customer Insights • Develop anomaly detection models for logistics and fleet operations • Identify patterns such as fuel inefficiencies, underutilized vehicles, abnormal trips, and driver behavior drift • Build proactive insight systems that surface recommendations automatically
Industry Benchmarking & Intelligence • Create benchmarking models comparing fleets across industries, vehicle types, and usage patterns • Develop scoring and performance indicators for customers • Build customer persona-based insights (Operations, Finance, Fleet Managers, etc.)
Work with Large-Scale IoT Data • Process high-volume telematics data (GPS, trips, fuel, sensors, orders, etc.) • Build data pipelines for training and inference • Design scalable model deployment and monitoring systems
Productionize Machine Learning Models • Deploy models into production systems • Monitor model performance and data drift • Continuously improve model accuracy and relevance
Collaborate Across Teams • Work closely with Product, Data, and Engineering teams • Translate business problems into ML solutions • Help shape the company’s AI roadmap
Must Have • 3+ years experience in Machine Learning or Data Science roles • Strong Python skills (Pandas, NumPy, Scikit-Learn, etc.) • Experience with time-series data or anomaly detection • Experience working with large datasets and data pipelines • Understanding of model deployment and production environments • Strong problem-solving and analytical thinking
Nice to Have (But Not Required) • Experience with IoT, telematics, or logistics data • Experience with forecasting or time-series models • Experience with clustering, anomaly detection, or unsupervised learning • Experience with cloud platforms (AWS, GCP, etc.) • Experience with real-time or streaming data systems