Data Scientist

Key Responsibilities :Develop, train, and optimize machine learning models for demand–supply prediction, route optimization, and customer/driver churn analysis.Implement predictive pipelines using structured and unstructured transportation data (GPS, sensor, transactional, behavioral).Collaborate with product and engineering teams to integrate ML models into production systems.Conduct exploratory data analysis (EDA) to identify key features, correlations, and anomalies in transportation datasets.Apply machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch) to prototype and deploy AI models.Perform model validation, testing, and monitoring to ensure reliability and scalability in real-world use cases.Support data engineers in building scalable data pipelines and maintaining data quality.Document model design, performance metrics, and deployment processes for team knowledge sharing.Requirements :Bachelor’s degree in Computer Science, Data Science, Statistics, or related field.3–5 years of experience in applied data science or machine learning engineering.Solid knowledge of supervised/unsupervised learning, regression, classification, clustering, and time-series forecasting.Hands-on experience in Python (pandas, scikit-learn, TensorFlow/PyTorch), SQL, and cloud environments (GCP/AWS/Azure).Familiarity with MLOps practices (CI/CD for ML, model versioning, monitoring).Strong problem-solving skills with ability to handle large-scale, imbalanced transportation datasets.Good communication skills to collaborate with cross-functional teams.