ML Operations Lead

Role Overview

ML Operations Lead

Key Responsibilities

• Lead and mentor the ML Operations team.
• Manage model deployment, monitoring, retraining, and rollback.
• Implement drift detection and model performance monitoring.
• Manage model validation, backtesting, champion-challenger testing, and model lineage.
• Monitor model metrics such as AUC and precision-recall.
• Collaborate with Data Engineering, Business teams, and Singapore leadership.
• Ensure model quality, fairness, and operational stability.

Must-Have Skills

• 8+ years of experience in ML/MLOps/Data Science Engineering, including team leadership.
• Hands-on experience with production ML models and

  Customer Churn models

  .
• Strong expertise in MLOps, model deployment, monitoring, drift detection, and retraining.
• Experience with CI/CD pipelines, model registries, lineage, and model validation.
• Knowledge of AUC, precision-recall, backtesting, and champion-challenger techniques.
• Excellent communication and stakeholder management skills.
• Bachelor's degree in Computer Science, Data Science, Engineering, Statistics, or a related field.
• Minimum 2 years of tenure with an organization preferred.

Preferred:

Interview Process:

Important: