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Head of Data Architecture

Short Description

The Head of AI Factory is responsible for shaping and executing the organization’s data science and artificial intelligence (AI) strategy. This role leads the development and deployment of advanced analytics, machine learning models, and data-driven solutions that enable smarter decision-making, improve risk management, and enhance customer experiences. The Head of AI Factory acts as a trusted advisor to senior executives and drives a culture of innovation and data-driven decision-making across the organization

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Responsibilities:

Overall accountable for:

  • Defining action plans related to Data Architecture and associated strategic initiatives.

  • Establishing governance frameworks, operating procedures, and supporting documentation for Data Architecture activities, including the Data Architecture Board (DAB) / Design Approval Board.

  • Defining and proposing the target Enterprise Data Architecture for VPBank at the conceptual design level.

  • Designing target data architecture solutions for specific Change Requests (CRs) and projects at the logical and physical design levels.

  • Collaborating with teams within the Enterprise Data Architecture function and relevant stakeholders to deliver data-related initiatives, projects, and change requests.

  • Providing strategic advisory to senior management on emerging data technologies and recommending suitable solutions for VPBank.

Ultimately accountable for:

  • Establishing quality assurance and control mechanisms; overseeing and approving work execution outcomes.

  • Measuring team performance and continuously improving processes, productivity, and operational efficiency.

Ultimately accountable for talent and team management in:

  • Enterprise Architecture.

  • Data Architecture.

  • Other architecture-related disciplines as assigned.

Additional responsibilities:

  • Leading and delivering special projects and strategic initiatives assigned by senior management.

Short Description

Requirements

•           Master’s or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, or related field.

•           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.

•           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.
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