Data Scientist with ML Engineering

Job Summary

Seeking a Data Scientist with ML Engineering expertise, the fully remote position will manage the entire machine learning model lifecycle, including development, deployment, and monitoring, while collaborating with cross-functional teams to drive business outcomes.

Key Responsibilities

• Develop, train, and evaluate machine learning models to address business challenges across various domains
• Own the full ML lifecycle, including data preparation, feature engineering, model training, validation, deployment, and monitoring
• Build and maintain MLOps pipelines using AWS SageMaker Studio, ensuring efficient experiment tracking and automated workflows

Required Qualifications

• 3+ years of experience in data science or a closely related role, with a focus on ML engineering and MLOps
• Strong proficiency in Python for data science and ML development, including libraries like pandas, scikit-learn, and PyTorch or TensorFlow
• Hands-on experience with AWS SageMaker Studio for model development and deployment
• Solid understanding of MLOps principles, including model versioning and production monitoring
• Experience with SQL and working with structured data in cloud data warehouses or relational databases