Head of Enterprise Data AI/Database/Data Science

KEY RESPONSIBILITIES
1. Data & AI Strategy
Define and execute the enterprise Data & AI strategy and multi-year roadmap aligned with business and technology priorities.
Translate business ambitions into strategic Data & AI initiatives, investments and measurable outcomes.
Drive the transformation toward a data-driven and AI-powered securities and investment platform.
Advise executive management on Data & AI opportunities, emerging technologies and strategic priorities.
2. Enterprise Data Foundation
Build and operate a unified enterprise data platform that brings together customer, account, trading, portfolio, cash, margin, market, product and operational data from VPBankS's core systems and digital platforms.
Establish real-time and historical data capabilities to support management reporting, business analytics, customer experiences, risk management and AI/ML use cases.
Develop trusted and reusable Data Products for key business domains, enabling consistent use of data across Trading, Wealth, Investment Banking, Risk, Finance, Operations and Technology.
Make enterprise data easy to discover, access and consume through governed datasets, APIs and data services, reducing fragmented data extraction and duplicated reporting across the organization.
3. Analytics, Data Science & AI
Lead the development of AI-powered investment and trading capabilities as a strategic differentiator for VPBankS.
Develop AI capabilities for market analysis, stock analysis, investment insights, portfolio intelligence and personalized investment recommendations.
Build intelligent trading experiences including AI trading assistants, trading bots and AI-assisted trading decision support.
Develop algorithmic and quantitative trading capabilities, leveraging market data, order-book data, historical trading data and quantitative models for signal generation, execution strategies and trading optimization.
Apply AI and advanced analytics to understand investor behavior and deliver hyper-personalized trading and investment experiences.
4. Data Governance
Establish enterprise-wide governance to ensure data quality, ownership, security, privacy and regulatory compliance.
Ensure critical business data has clear accountability and appropriate controls throughout its lifecycle.
Establish appropriate governance for AI models, enterprise AI usage and Responsible AI.
Promote a culture where trusted data is treated as a strategic enterprise asset.
5. Organization & Leadership
Build and lead a high-performing Enterprise Data & AI organization covering Data Engineering, Analytics, Data Science, Data Governance and AI.
Define the organization structure, operating model, talent strategy and capability development roadmap.
Establish strong engineering, delivery and governance disciplines across Data & AI teams.
Develop senior Data & AI leaders and build sustainable internal capabilities.
Manage strategic technology partners, vendors and Data & AI investments.
KEY ACCOUNTABILITIES
The Head of Enterprise Data & AI will ultimately be accountable for:
Trusted enterprise data available for critical business and regulatory needs.
Scalable Data & AI platforms capable of supporting the company's growth.
Measurable business value generated from Analytics, Data Science and AI.
Enterprise-wide Data Governance and responsible use of AI.
Data & AI adoption across business and technology.
Building a world-class Data & AI organization and talent base.