Organization: Orient Commercial Joint Stock Bank (OCB)
Position: Model Operations Specialist – Data Science Division
Location: Ho Chi Minh City, Vietnam
Employment Type: Full-time
Experience Required: 1–5 years
Application Deadline: July 15, 2026
Salary: Competitive

About the Position

The Data Science Division of OCB is seeking a Model Operations Specialist to support the deployment, monitoring, and lifecycle management of machine learning models in a production environment. This role is ideal for candidates with a strong background in Data Science, MLOps, DevOps, Data Engineering, or Software Engineering who are passionate about building reliable and scalable AI systems.

Key Responsibilities

• Establish and standardize MLOps best practices, including feature stores, CI/CD pipelines, model metadata repositories, and operational governance frameworks.
• Develop and maintain monitoring and reporting systems to track model performance and operational effectiveness.
• Manage daily business-as-usual (BAU) activities related to model deployment, operation, and performance monitoring throughout the model lifecycle.
• Lead and participate in research and training initiatives related to MLOps maturity assessment frameworks, open-source MLOps solutions, and emerging technologies.
• Develop policies, standards, and procedures governing MLOps and Data Science activities, ensuring compliance across all related artifacts and workflows.
• Perform other duties as assigned by management.

Requirements

• Bachelor’s degree or higher in Computer Science, Data Science, Information Technology, Engineering, or related fields.
• At least 2 years of experience in Data Science, DevOps, Software Engineering, or Data Engineering.
• Strong teamwork, communication, and problem-solving skills.
• Ability to work carefully, logically, and effectively under pressure.
• Knowledge of database systems, including SQL and NoSQL.
• Experience with commercial machine learning platforms such as AWS, Azure, Databricks, or other cloud services is an advantage.
• Familiarity with at least one machine learning framework, such as Scikit-learn, PyTorch, or TensorFlow.
• Understanding of system architecture and big data platforms (e.g., Hadoop).
• Proficiency in Linux, Docker, Kubernetes, and system scaling techniques.
• Candidates with experience building and operating end-to-end MLOps platforms, including data ingestion, workflow orchestration, model training, model/data drift monitoring, model registry, model serving, and feature stores, will be given preference.
• Experience in the banking or financial services industry is a plus.

Benefits

• Competitive compensation package.
• Laptop and necessary working equipment.
• Comprehensive insurance and healthcare programs.
• Annual salary review and performance bonuses.
• Professional training and career development opportunities.
• Business travel allowances and seniority benefits.
• Annual leave and company-sponsored activities.
• Sports clubs and employee wellness programs.

Candidate Profile

This opportunity is particularly suitable for graduates and professionals interested in Machine Learning Operations (MLOps), Data Engineering, Cloud Computing, AI Platform Engineering, and Enterprise Data Science systems.

Students and alumni with strong technical foundations in machine learning deployment, cloud platforms, containerization technologies, and data engineering are encouraged to apply.