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Open nowFirst seen 14 days ago

AI Director

newbridge93 open roles

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Your applicationOpen nowAI Directornewbridge

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The clock on this job

Early applications get read.

13.8% of postings close within 7 days. Measured by our own scanner across the market. newbridge postings stay open a median of 11 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.7%3 days
  3. 13.8%7 days
  4. 22.3%14 days
  5. 37.8%30 days
  6. 59.0%60 days
This job: first seen 14 days ago

newbridge median: 11 days open

The posting

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.
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