Data Scientist

You will be responsible for building, training, evaluating, and deploying machine learning models in production environments. This includes managing the complete ML lifecycle, from data collection and preprocessing to feature engineering and model training. Key Responsibilities: - Deploy and monitor models using MLOps tools and frameworks - Design and maintain scalable MLOps pipelines and processes - Implement model monitoring and performance tracking using observability tools - Handle model retraining and continuous improvement strategies - Work with big data systems for processing and analytics - Collaborate with cross-functional teams in Agile environments - Ensure model governance, versioning, and reproducibility Qualifications Required: - Solid experience in building and deploying machine learning models - Proficiency in data preprocessing, feature engineering, and model training - Familiarity with MLOps tools and frameworks - Strong skills in model monitoring and performance tracking - Experience with big data systems for processing and analytics - Ability to collaborate effectively with cross-functional teams in Agile environments You will be responsible for building, training, evaluating, and deploying machine learning models in production environments. This includes managing the complete ML lifecycle, from data collection and preprocessing to feature engineering and model training. Key Responsibilities: - Deploy and monitor models using MLOps tools and frameworks - Design and maintain scalable MLOps pipelines and processes - Implement model monitoring and performance tracking using observability tools - Handle model retraining and continuous improvement strategies - Work with big data systems for processing and analytics - Collaborate with cross-functional teams in Agile environments - Ensure model governance, versioning, and reproducibility Qualifications Required: - Solid experience in building and deploying machine learning models - Proficiency in data preprocessing, feature engineering, and model training - Familiarity with MLOps tools and frameworks - Strong skills in model monitoring and performance tracking - Experience with big data systems for processing and analytics - Ability to collaborate effectively with cross-functional teams in Agile environments