Manager: Data Science

Role overview

CredTech, a wholly owned subsidiary of MTN Group FinTech, is aiming to become Africa’s leading digital lending platform. The business is built around strong delivery in technology and commercial execution, with a focus on improving credit scoring, speeding up product launch cycles, and strengthening debt and risk management through strategic partnerships.

This role is for a Manager: Data Science within CredTech. The successful candidate will play a key part in shaping and scaling the company’s data science capabilities as the business grows.

What you will do

• Build, develop, deploy and optimise machine learning models, analytical workflows and supporting systems used across CredTech’s products and services.
• Create production-grade solutions for credit risk, behavioural scoring, decisioning, portfolio optimisation and operational analytics.
• Support scalable MLOps practices, including data pipelines, model monitoring, API-based deployment and controlled use of AI-enabled tools.
• Work in a hybrid technology landscape that includes Azure-based tools such as Azure AI Foundry where relevant, alongside partner environments that run on Linux and are centred on Python.

Required background

• A minimum four-year tertiary qualification in Computer Science, Mathematics, Statistics, Data Science, Engineering, Finance, Commerce, Statistical studies or a closely related discipline.
• Between 5 and 8 years of relevant experience in machine learning engineering, data science, decision science, MLOps or analytics engineering.
• At least 2 to 3 years of practical experience delivering applied machine learning, model deployment, data science workflows or MLOps capabilities.
• Strong hands-on ability in Python, SQL, Linux-based development environments and current machine learning / data science libraries.
• Experience writing production code, APIs, batch jobs, data pipelines or model inference workflows.
• Working knowledge of Git, CI/CD, Docker, Kubernetes, microservices and API-driven deployment methods.
• Experience collaborating with product, data engineering, credit risk, operations, technology and market teams.
• English fluency is required; French, Chinese and African languages are an advantage.

Preferred qualifications and experience

• A master’s degree in Computer Science, Data Science, Statistics, Finance, Commerce, Engineering or a related area.
• Professional certification in AI/ML, cloud, MLOps, Azure or data science.
• Background in fintech, banking, consumer finance, telecommunications, digital lending, payments or broader financial services.
• Experience building and rolling out credit risk models, behavioural models, affordability models, decisioning systems or portfolio analytics.
• Exposure to Azure-based AI/ML platforms such as Azure ML and/or Azure AI Foundry.
• Familiarity with MLOps tools such as MLflow, Kubeflow, Azure ML, model registries, experiment tracking or monitoring solutions.
• Working knowledge of Hadoop, Spark, PySpark or similar distributed processing frameworks.
• Exposure to reinforcement learning, optimisation, simulation or policy testing.
• Experience with LLM-based tools, agentic workflows, prompt engineering or AI-assisted development.
• Experience working across multiple markets, cultures, vendors, partners and technology environments.

Additional information

Location: Dubai, United Arab Emirates.

Application closing date: 22 June 2026. Late applications will not be accepted.

If you do not receive feedback within 2 weeks after the closing date, you should consider the application unsuccessful.