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Dangote Industries Limited Linkedin · Posted 2d ago

Group Head - Artificial Intelligence & Digital Transformation

Lagos

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Dangote Industries Limited Job Summary:

  • The Group Head: AI & Digital Transformation is responsible for defining and executing the Group’s enterprise-wide Artificial Intelligence and Digitisation strategy, translating emerging technologies into measurable improvements in operational performance, reliability, productivity, safety, risk management and commercial value.
  • The role will identify, prioritise and scale high-value AI and digital use cases across the Group’s industrial portfolio, including refining, petrochemicals, fertiliser, cement, manufacturing, mining/raw materials, logistics, transport, supply chain and corporate functions.
  • The role will lead the development and deployment of AI-enabled solutions including machine learning, predictive and prescriptive analytics, computer vision, optimisation algorithms, generative AI, intelligent automation, digital twins and advanced decision-support systems.
  • The Group Head will operate at the intersection of business, industrial operations, data, technology and AI, working closely with the GCRO, GCIO, business CEOs/MDs, plant leadership and functional executives. The role will ensure that AI and digitisation investments move beyond experimentation to production-scale solutions with defined business outcomes, appropriate governance and measurable return on investment.
  • AI & Digitisation is a centre-led Group capability, with execution embedded across business units and operating environments

Qualifications & Experience

  • Bachelor’s degree in Artificial Intelligence, Computer Science, Data Science, Machine Learning, Software Engineering, Computer Engineering, Electrical/Electronic Engineering, Robotics,
  • Mathematics, Statistics, Computational Science or related quantitative discipline.
  • Master’s degree in Artificial Intelligence, Machine Learning, Computer Science, Data Science, Engineering, Robotics or a related advanced technology discipline strongly preferred.
  • Executive education in technology, innovation, digital transformation or business strategy would be advantageous.
  • 10+ years’ relevant technology/data/AI experience, with meaningful leadership responsibility and evidence of deploying advanced technology into production environments.
  • Demonstrable experience taking AI solutions from problem definition and data engineering through model development, deployment, monitoring and value realisation.
  • Experience in industrial, energy, oil & gas, manufacturing, utilities, mining, logistics, infrastructure or other asset-intensive environments strongly preferred.
  • Experience building or leading multidisciplinary teams comprising data scientists, ML engineers, data engineers, software engineers, product specialists and business/industrial SMEs.
  • Demonstrable portfolio of successfully deployed AI/digital products with quantifiable operational or financial outcomes

Key Requirements

  • Advanced understanding of machine learning, deep learning, generative AI, large language models and advanced analytics.
  • Strong understanding of Python, SQL and modern AI/ML development environments; technical credibility sufficient to interrogate models, architectures and algorithms.
  • Understanding of time-series modelling, forecasting, optimisation, anomaly detection and predictive modelling.
  • Knowledge of computer vision, NLP, intelligent automation and agentic AI systems.
  • Understanding of digital twins, IoT, edge computing, sensors and industrial data environments.
  • Strong understanding of MLOps, model deployment, APIs, cloud platforms, data pipelines and model monitoring.
  • Ability to apply AI to rotating equipment, process plants, production optimisation, asset integrity, reliability and industrial risk.
  • Ability to translate complex industrial and business problems into mathematical, analytical and AI-solvable problems.
  • Strong commercial orientation with ability to quantify ROI, productivity gains, avoided losses, downtime reduction and margin improvement.
  • Strong understanding of AI governance, model risk, data privacy, cybersecurity and responsible AI.
  • Exceptional strategic thinking, innovation, stakeholder influence and executive communication.
  • Ability to challenge technology hype and distinguish between automation, analytics, digitisation and genuine AI applications.a
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