- Type
- Full-time
- Seniority
- Director
- Education
- PhD
- Closing date
- Today
- Source
- CareersPage
Description
Head of Data & AI Strategy
We are seeking a visionary and execution-driven Head of Data & AI to shape and drive our client's enterprise-wide Data and Artificial Intelligence roadmap. In this high-impact executive leadership role, you will lead the data strategy, build scalable analytics infrastructure, and pioneer pragmatic AI/ML solutions that directly drive revenue growth, elevate customer engagement, and streamline core operations.
Key Responsibilities
1. Strategic Leadership & Business Alignment
- Formulate and execute a comprehensive enterprise Data & AI strategy, investment roadmap, and governance framework aligned with core business growth objectives.
- Identify high-value opportunities to leverage advanced analytics, predictive modeling, and generative AI to accelerate top-line revenue, reduce churn, and optimize operating margins.
- Serve as a strategic advisor to executive leadership, bridging technical possibilities with commercial execution.
2. Data Architecture & Infrastructure Excellence
- Oversee the modern data architecture, scalable platform infrastructure, and high-performance analytics ecosystem.
- Establish robust data governance, master data management, security protocols, and regulatory compliance standards across all data touchpoints.
- Ensure data reliability, accessibility, single-source-of-truth standards, and self-service analytics capabilities organization-wide.
3. Advanced AI / ML & Intelligent Automation
- Lead end-to-end design, deployment, and optimization of production-grade machine learning models, Generative AI (LLMs), and intelligent AI agents.
- Architect business-focused solutions including recommendation engines, predictive behavior analytics, automated catalog/entity management, and process automation.
- Measure and optimize model efficacy, compute costs, scalability, and overall ROI of AI investments.
4. Cross-Functional Partnership & Business Impact
- Partner closely with Product, Engineering, and Business Unit leads to turn complex commercial challenges into actionable, data-driven solutions.
- Define clear KPIs and establish clear ROI tracking for all data and machine learning initiatives.
5. Team Building & Operational Management
- Mentor, scale, and lead a high-performing department of 25–30 multi-disciplinary professionals (Data Engineers, Data Scientists, and Data Analysts).
- Foster a performance-driven culture emphasizing technical excellence, business acumen, and rapid experimental iteration.
- Champion responsible AI principles, data privacy, and ethical technology practices.
Target Experience & Qualifications
- Education: Master's or Ph.D. in Computer Science, Applied Mathematics, Data Science, Statistics, Economics, or a closely related quantitative field.
- Leadership Experience: Proven track record in progressive Data & AI leadership roles, managing cross-functional technical teams (Data Science, Engineering, and Analytics).
- Technical Depth: Deep expertise in modern data platform architecture, data warehousing, analytics infrastructure, MLOps, and AI/ML ecosystems.
- Advanced AI Knowledge: Strong hands-on familiarity with Python, SQL, modern machine learning frameworks, Generative AI architectures, LLMs, and AI agent frameworks.
- Commercial Acumen: Exceptional strategic thinking and business acumen with a proven ability to translate complex data concepts into measurable financial and operational outcomes.
- Communication: Outstanding executive presence, communication skills, and stakeholder management capability.
- Domain Expertise (Preferred): Experience within B2B SaaS, Retail Technology, E-commerce, Merchant Solutions, or Fintech ecosystems is a strong advantage.