Data Analytics & ML Ops Engineer

Responsibilities:

1. Develop and manage analytics and ML pipelines covering data preparation, model deployment, and orchestration in production environments.
2. Operationalize machine learning models by integrating models into data platforms, applications, and business workflows.
3. Monitor model performance, data drift, and pipeline reliability to ensure stability, accuracy, and continuous improvement.
4. Collaborate with data scientists and data engineers to standardize deployment, versioning, and experimentation practices.
5. Strengthen MLOps and analytics engineering standards including automation, documentation, and operational controls.

Requirements:

• Bachelor’s Degree in Computer Science, Data Engineering, Information Systems, or related fields.
• Master’s Degree in Data Engineering or AI is an advantage.
• 3–6 years of experience in data engineering, analytics engineering, or MLOps roles.
• Experience with cloud-based analytics platforms and ML deployment in production environments
• Experience in Telco industry is a plus.