Senior Manager - Data Scientist.Group Strategy and Transformation at MTN

Responsibilities

Model Design & Development: 

• Lead the development of advanced machine learning models and AI frameworks that leverage telco, geolocation, and behavioural signals.
• Define modelling standards and promote reuse of pipelines, features, and architectures across multiple use cases.

AI Solution Packaging: 

• Architect AI-enabled components that can be operationalised as scalable products or consulting accelerators across OpCos.
• Guide the modularisation of ML solutions for deployment in different sectors (e.g. financial services, retail, government).

Use Case Leadership & Translation:

• Engage with executive and business stakeholders to identify high-impact use cases aligned to commercial and operational KPIs.
• Define the success criteria, data requirements, and validation frameworks that underpin each AI initiative.

MLOps and Deployment: 

• Partner with Engineering and DevOps to ensure seamless model deployment into production environments using modern CI/CD, containerisation, and MLflow/Kubeflow pipelines.
• Embed traceability, auditability, and scalability as core principles of ML deployment practices.

Model Monitoring & Ethics:

• Lead efforts to track model health, bias, drift, and fairness in accordance with Responsible AI and ethical governance frameworks.
• Define audit protocols and escalation paths for AI risk mitigation and regulatory compliance.

Cross-functional Collaboration: 

• Serve as the AI representative within multidisciplinary squads, aligning workstreams across Data Engineering, Product, Governance, and Commercial teams.
• Translate technical complexity into strategic narratives that influence senior leadership and client stakeholders.

Leadership & Innovation Expectations

• Champion a data science culture of experimentation, intellectual curiosity, and measurable business value.
• Drive innovation in AI use cases, including real-time intelligence, geospatial modelling, and deep learning frameworks.
• Build communities of practice for AI excellence across MTN OpCos.
• Represent MTN DataCo in regional and global forums to promote leadership in responsible and impactful AI applications

Qualifications

Job Requirements (Education, Experience and Competencies)

Education:

• 4 year degree in Computer Science, Statistics, Applied Mathematics, Data Science, or a related quantitative field (required)
• Master’s degree or PhD in Machine Learning, Artificial Intelligence, or a relevant discipline (preferred)
• Certifications in machine learning, cloud AI services (e.g. GCP ML, Azure AI, Databricks), or Responsible AI frameworks (advantageous)

Experience:

• Minimum of 5 - 8 years of progressive experience in data science, AI/ML solution development, or advanced analytics, with a proven record of production-grade deployments
• At least 3+ years in a senior leadership or team lead role guiding AI initiatives in enterprise settings
• Demonstrated success in developing and scaling AI/ML solutions using telco, location, or behavioural datasets
• Strong experience working in cloud-based MLOps environments (e.g. Azure ML, GCP Vertex AI, Databricks, MLflow/Kubeflow)
• Exposure to cross-sector AI deployments, including financial services, retail, or public sector use cases, is highly advantageous
• Proven track record of working in agile, cross-functional teams, ideally in platform, product, or consulting environments
• Prior experience in telco, urban planning, consulting, or retail analytics domains
• Demonstrated experience with big data datasets in customer behaviour, geospatial, etc.
• Proven ability to deploy models into production and monitor at scale

Competencies:

• ML & AI Expertise: Deep understanding of supervised/unsupervised learning, time series, recommendation systems, classification, NLP, and spatial ML
• Solution Packaging: Ability to abstract models into reusable components, APIs, or solution accelerators
• MLOps Proficiency: Practical experience with model versioning, testing, orchestration, and monitoring in production
• Responsible AI & Ethics: Working knowledge of fairness, bias detection, explainability, and AI risk governance
• Strategic Translation: Strong business acumen with ability to align technical work to commercial and operational outcomes
• Technical Leadership: Capable of mentoring junior data scientists and leading architectural discussions
• Communication & Influence: Clear communicator who can engage C-level audiences and simplify technical concepts for non-technical stakeholders

Key Deliverables:

Internal:

• Enterprise-grade ML Models: Deployed predictive and prescriptive models that directly inform business-critical decisioning across Group and OpCos (e.g., churn prediction, product affinity, fraud detection).
• Reusable AI Pipelines: Production-ready ML pipelines and feature stores, complete with automated retraining, performance monitoring, and MLOps documentation to support cross-functional reuse and scalability.
• Strategic AI Use Case Portfolio: Curated catalogue of prioritised, high-impact AI use cases mapped to business KPIs, with supporting artefacts (problem statements, data assets, success metrics, and outcome reports).
• Responsible AI & Governance Artefacts: Integrated bias assessment reports, fairness validations, and model documentation aligned to MTN’s AI governance standards.

External:

• Client-ready AI Assets: Sector-specific AI solutions (e.g., footfall prediction, customer lifetime value, geospatial targeting) embedded in MTN’s PoV and consulting engagements.
• Commercialised AI Offerings: Packaged machine learning modules and APIs contributing to MTN DataCo’s product catalogue and monetisation platforms.
• Thought Leadership Contributions: Insight briefs, client presentations, and published use cases that position MTN as a pan-African leader in responsible and applied AI.
• Partner Integration Support: Technical documentation and onboarding artefacts enabling secure and scalable integration of AI components into client or partner environments.

Apply Before 10/13/2025