Description

You will build and manage customer-centric machine learning models to drive customer segmentation and reduce churn.

Responsibilities

• Automate model training, validation, and deployment pipelines using Databricks Workflows.
• Track experiments, log metrics, and manage the full model lifecycle with MLflow.
• Register, version, and manage production models using the Databricks Model Registry.
• Implement model monitoring and logging to track performance and identify production issues.
• Execute model versioning and rollback strategies to ensure smooth updates.
• Collaborate with data scientists to integrate models into production environments.

Required Skills

• 12+ years of professional experience.
• Deep proficiency with Databricks Workflows for pipeline automation.
• Hands-on experience with MLflow for experiment tracking and lifecycle management.
• Experience using Databricks Model Registry for versioning and deployment.
• Practical knowledge of MLOps best practices for scalability and monitoring.
• Understanding of ETL pipelines and data engineering concepts.
• Ability to work within 9-5 ET time zone.
• Any graduate degree.

Key Skills

Education

Any Gradute