Artificial Intelligence & Digital Transformation Analyst at Dangote

Job Summary

• The Artificial Intelligence & Digital Transformation Analyst is responsible for supporting the identification, development, testing, deployment and performance monitoring of AI and digital solutions across the Group.
• Unlike a conventional business analyst role, this is intended to be a technically capable AI role. The Analyst will work with business and plant teams to understand operational problems, interrogate data, develop analytical and machine-learning models, test algorithms and support the conversion of successful prototypes into deployed solutions.
• The role will work across industrial operations, machinery, maintenance, production, logistics, transport, commercial and corporate functions, supporting the Group’s ambition to use AI and digitisation to improve productivity, reliability, safety, resilience and decision-making.

Job Responsibilities

• Identify business and operational problems suitable for AI and digital solutions.
• Work with business and plant teams to understand operational challenges and requirements.
• Analyse and interrogate data to support AI and machine-learning initiatives.
• Develop, test and evaluate analytical and machine-learning models.
• Support the development and deployment of AI and digital solution prototypes.
• Monitor the performance of deployed AI and digital solutions.
• Apply AI, machine learning and advanced analytics to improve productivity, reliability, safety and decision-making.
• Translate technical outputs into clear operational and commercial recommendations.
• Work closely with engineers, operators and plant leadership across the Group.
• Support the Group AI & Digitisation programme and its implementation across business units and plants.

Requirements

Qualifications & Experience

• Bachelor’s degree in Artificial Intelligence, Machine Learning, Computer Science, Data Science, Software Engineering, Computer Engineering, Electrical/Electronic Engineering, Robotics, Mathematics, Statistics or related quantitative discipline.
• Master’s degree in AI, Machine Learning, Data Science or related field would be advantageous.
• Relevant practical certifications in machine learning, cloud AI, data engineering, MLOps or industrial analytics would be advantageous.
• 3 - 6 years’ relevant experience in AI, data science, machine learning, advanced analytics or digital product development.
• Evidence of hands-on model development, whether through commercial deployments, research, engineering projects or a strong technical portfolio.
• Exposure to manufacturing, industrial, energy, logistics or other asset-intensive environments would be advantageous

Functional & Technical Competencies

• Strong working capability in Python and SQL.
• Practical experience with modern machine-learning frameworks and libraries.
• Ability to develop regression, classification, clustering, forecasting and anomaly-detection models.
• Understanding of neural networks/deep learning and generative AI/LLMs.
• Exposure to computer vision and image/video analytics.
• Understanding of time-series and industrial sensor data.
• Ability to design, train, test and evaluate machine-learning models and algorithms.
• Understanding of APIs, databases, data pipelines, cloud platforms and MLOps principles.
• Exposure to IoT/IIoT, industrial automation, digital twins or OT environments would be highly advantageous.
• Strong analytical and mathematical problem-solving capability.
• Ability to translate technical outputs into clear operational and commercial recommendations.
• Strong curiosity and experimentation mindset, balanced by disciplined model validation and governance.
• Ability and willingness to work directly with engineers, operators and plant leadership at operating sites.