DATA SCIENTIST

Job Summary

Build, train, and validate machine learning models. Develop automated workflows for model inference and post-processing. Optimize production ML pipelines for performance and scalability. Manage model artifacts, versions, and metadata using GCS and model registries. Support production monitoring, model quality, and reliable inference operations.

Required Skills and Experience

• Strong Python programming for Data Science and Machine Learning.
• Hands-on experience with PyTorch, scikit-learn, CatBoost, or similar ML frameworks.
• Experience with Google Cloud Vertex AI for model training and validation.
• Hands-on knowledge of Kubernetes and Argo Workflows.
• Strong understanding of feature engineering, EDA, model evaluation, and validation.
• Experience deploying models for production inference.
• Knowledge of MLOps, model versioning, monitoring, and lifecycle management.
• Familiarity with model drift detection, retraining strategies, and CI/CD for ML pipelines.

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