Job Specifications
South Pole is an energetic, global company offering comprehensive sustainability solutions and services. With offices spanning all continents across the globe, we strive to create a sustainable society and economy that positively impacts our climate, ecosystems and developing communities. With our solutions, we inspire and enable our customers to create value from sustainability-related activities.
Job summary:
We are looking for a high-impact Head of Data & AI to serve as our lead architect and strategist for AI adoption as well as lead our Data and Insights team. This is a senior role for an AI leader who understands that an AI strategy is only as good as the data infrastructure supporting it. You will be the bridge between our raw data silos and actionable AI implementation, working cross-functionally to prepare our environment for enterprise-scale AI. This role requires a leader who can define a high-level AI strategy, manage the tactical roadmap, and roll up their sleeves to oversee the operational deployment of AI-driven products and processes.
Main tasks & responsibilities:
Strategic (Vision & Alignment)
AI Opportunity Mapping: Identify and prioritize high-impact areas across the business where AI can drive revenue or efficiency. Design the roadmap and bring to implementation while partnering with the Business Lines/Functional AI champions
Executive Advisory: Act as the primary subject matter expert for the leadership team on AI trends, risks, and competitive advantages.
Governance & Ethics: Develop frameworks for responsible AI use, ensuring data privacy, transparency, and compliance with emerging regulations.
Tactical (Planning & Architecture)
Portfolio Management: Manage a pipeline of AI projects from "Proof of Concept" (PoC) to full-scale production.
Cross-Functional Collaboration: Be the sparring partner to the Business Leads and AI champions on the AI efficiencies and implementation in the business context. Partner with Product, Engineering, and Data teams to ensure AI initiatives are technically feasible and aligned with the core product.
Data Readiness Audit: Evaluate and map disparate data sources across the organization to determine "AI-readiness" (quality, labeling, and accessibility).
Infrastructure Design: Architect the "AI Pipeline"—identifying the necessary data sources, vector databases, and MLOps tools needed to move from local pilots to production.
Operational (Execution & Delivery)
Lead AI Implementation: Oversee the day-to-day progress of AI developments, removing blockers and ensuring high-quality output.
Performance Monitoring: Define and track KPIs for all deployed models.
Organizational Upskilling: Partner with People and Culture on the Organizational upskilling program to ensure the AI adoption is broad, including internal workshops and training to upskill non-technical staff on how to use AI tools effectively in their daily workflows. In collaboration, design dedicated online education channels and measure the adoption.
Stakeholder Navigation: Act as the primary liaison between technical teams (IT, Engineering) and business units and support functions Legal, Marketing, People and Culture and other, to align AI goals.
Change Advocacy: Educate and influence senior leadership on the reality of AI timelines, specifically managing expectations regarding data cleaning and infrastructure setup. Bring in the positive change in the changing jobs scoping and efficiencies driven by AI implementation.
ROI Modeling: Work with finance and department heads to quantify the impact of AI initiatives on the bottom line.
Leadership
Team Leadership & Mentorship: Direct management of the Data & Insights team, transitioning them from traditional reporting/BI to an "AI-first" mindset through active coaching and technical upskilling.
Data Lifecycle Ownership: Oversee the end-to-end data pipeline—from ingestion and cleaning to advanced analytics—ensuring the team delivers high-quality datasets that serve as the foundation for organizational strategy.
Modernizing the Stack: Lead the evolution of the team's toolkit, moving from static dashboards to predictive insights and automated data delivery systems.
Performance & Impact Culture: Define and implement rigorous standards for data accuracy and project delivery, ensuring the team's output directly correlates to business KPIs and strategic decision-making.
Cross-Pollination of Expertise: Facilitate collaboration between the Data team and other business units to ensure insights are not siloed, but are instead integrated into the operational workflows of the entire organization.
Requirements:
Experience: 8+ years in technology leadership, with at least 3+ years specifically focused on implementing Machine Learning or Generative AI solutions.
Technical Fluency: Deep understanding of the AI lifecycle (data preparation, fine-tuning, RAG architecture, and deployment). While you may not code daily, you can conduct a technical review of an architec
About the Company
South Pole is the world's leading carbon asset developer and climate consultancy.
Since 2006, South Pole has been a trusted partner and advisor to governments, public sector organisations, and leading businesses on their decarbonisation journeys. South Pole serves over 1,000 clients across the world, and its global team of experts has helped many Fortune 500 businesses implement comprehensive strategies that help build resilience and turn climate action into long-term business opportunities.
In line with its mission to del...
Know more