- Strategic Leadership
- Define and implement the enterprise-wide data science and AI strategy aligned with business priorities.
- Advise C-level executives on opportunities to leverage data for business growth, risk mitigation, and operational efficiency.
- Model Development & Innovation
- To executive high-value AI/ML initiatives across the organization.
- Lead the design, development, validation, and deployment of predictive models (e.g., credit scoring, fraud detection, risk forecasting, customer segmentation, personalized marketing).
- Oversee the governance and lifecycle management of all models to ensure accuracy, compliance, and sustainability
3. Data & Technology Architecture
- Collaborate with IT and Data Engineering to build scalable data platforms, pipelines, and AI/ML infrastructure (cloud, real-time analytics, data lakes).
- Ensure data quality, integrity, and accessibility across the enterprise.
- Governance & Compliance
- Establish ethical AI practices and ensure compliance with data privacy, regulatory, and security requirements.
- Business partnership
- Partner with business units to identify use cases and deliver measurable business impact.
- Translate complex analytical insights into clear, actionable recommendations for stakeholders.
5. People Management
- Implement the necessary leadership and management to enable direct and indirect subordinates to achieve the goals of the AI Factory.
- Head-count planning, human resource allocation. Work in collaboration with HR to develop recruitment, training, succession planning, career development roadmap, recognition employees, performance management for employees in the Department
6. Corporate Culture
- Act as a role model in building corporate culture. Ensure the correct and full implementation of corporate culture implementation plans; Employees understand and apply consistently corporate cultural values, behavioral standards of VPBank
Educational Qualifications
- Master’s or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, or related field.
Relevant Knowledge/ Expertise -
- 10+ years of experience in data science or advanced analytics, including at least 5 years in a leadership role.
- Proven track record of building and deploying machine learning and AI models in large-scale production environments.
- Expertise in statistical modeling, machine learning, deep learning, natural language processing, and big data technologies.
- Các Kỹ Năng, Năng lực /Skills and Competencies
- Proficiency in programming languages (Python, R, SQL) and experience with distributed computing (Spark, Hadoop) and cloud platforms (AWS, GCP, Azure).
- Strong leadership, stakeholder management, and communication skills, with the ability to influence at the executive level.
