Vietnam Silicon

Job Brief

We are looking for a visionary and experienced Head of Data/AI Center to lead the design and implementation of data and AI solutions that drive digital transformation across key sectors including finance, agriculture, and logistics. This role requires deep expertise in building large-scale data systems and deploying AI/ML solutions for complex, high-impact environments such as government agencies and large enterprises (e.g., banks).

Responsibilities

1. Define and execute a comprehensive data and AI strategy aligned with digital transformation solutions.
2. Lead the development of enterprise-wide data architecture, including big data platforms, data lakes, and AI/ML pipelines.
3. Design and oversee the implementation of scalable, distributed data systems capable of handling high-volume, real-time data.
4. Select and integrate appropriate technologies (e.g., Hadoop, Spark, Kafka, cloud platforms like AWS, Azure, GCP).
5. Lead the development of machine learning and AI models for use cases such as credit scoring (finance), crop yield prediction (agriculture), and route optimization (logistics).
6. Ensure AI solutions are explainable, ethical, and aligned with regulatory standards.
7. Build and manage high-performing teams of data engineers, data scientists, ML engineers, and analysts.
8. Foster a culture of innovation, collaboration, and continuous learning.
9. Collaborate with clients to understand their needs and deliver tailored data/AI solutions.
10. Ensure compliance with data privacy and security regulations (e.g., GDPR, local data laws).

Requirements

1. Bachelor’s or Master’s degree in Computer Science, Data Science, Applied Mathematics, or a related field.
2. 10+ years of experience in Data and AI roles, with at least 5 years in a senior leadership or manager level position.
3. Proven experience in building and scaling large-scale data platforms and deploying AI/ML solutions in enterprise or public sector environments.
4. Deep understanding of data architecture, data lakes, data warehousing, and real-time data processing.
5. Hands-on experience with big data technologies (e.g., Hadoop, Spark, Kafka), cloud platforms (AWS, Azure, GCP), and modern data tools (e.g., Snowflake, Databricks).
6. Strong knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and MLOps practices.
7. Familiarity with data governance, data privacy regulations (e.g., GDPR, local laws), and security best practices.
8. Demonstrated ability to lead and scale cross-functional teams including data engineers, data scientists, ML engineers, and analysts.
9. Strong people management skills: hiring, mentoring, performance management, and career development.
10. Proven track record of building a high-performance, motivated, and collaborative team culture.
11. Ability to inspire and align teams around a shared vision and strategic goals.
12. Excellent communication and stakeholder management skills, with the ability to translate complex technical concepts into business value.
13. Experience working with C-level executives, government stakeholders, and enterprise clients.
14. Strong problem-solving, critical thinking, and decision-making abilities.