integrate models into robust production systems, while continuously improving quality, relevance, reliability, and user value.Write clean, tested, production-quality Python and contribute reusable data science components, packages, and scalable data pipelines for preprocessing, inference, experimentation, monitoring, and continuous improvement.Support deployment, monitoring, model maintenance, drift detection, automated retraining, and ongoing … optimization of data science systems.Collaborate with engineering, product, UX, analytics, research, and domain experts, and communicate technical concepts, model behavior, insights, trade-offs, and recommendations clearly to technical and non-technical audiences.RequirementsExperience in data science, machine learning, artificial intelligence, NLP, statistics, applied mathematics, computer science ...