Manager: Data Science

Fintech is entering a new phase where operational and commercial excellence has become critical for success. We at MTN believe this is a game changer in terms of our business strategy. We are looking at an incumbent to join us as we build a successful business together.

As part of your portfolio as a
Manager: Data Science
you will:

• Lead the development and implementation of the
  AI and advanced analytics strategy
  , ensuring alignment with MTN Fintech's business objectives.
• Translate business needs into
  AI/ML use cases
  that deliver measurable impact (growth, efficiency, risk mitigation).
• Drive adoption of
  real-time and prescriptive analytics
  , embedding AI into decisioning and product workflows.
• Develop comprehensive implementation plans for data science projects, balancing innovation speed with governance.
• Build frameworks for
  AI readiness assessment
  , ensuring data quality, ethics, and infrastructure alignment.
• Provide analytical insight to shape product, marketing, and risk strategies.
• Foster partnerships with Group Technology and external AI/ML vendors to co-create scalable data solutions.
• Drive delivery of
  end-to-end machine learning pipelines
  from data ingestion to model deployment and lifecycle management.
• Execute
  AI-driven automation
  for fraud detection, customer segmentation, personalization, and pricing optimization.
• Leverage large-scale wallet and transactional data to identify patterns, forecast trends, and optimize risk strategies.
• Apply advanced analytics, including
  deep learning, NLP, computer vision, and graph analytics
  , to solve complex fintech challenges.
• Enable
  MLOps practices
  for model monitoring, retraining, and continuous delivery.
• Collaborate with data engineers to evolve next-generation data platforms (streaming, real-time data lakes).
• Build and scale
  AI-enabled APIs and microservices
  that plug directly into operational and customer-facing platforms.
• Drive
  data democratization
  by developing self-service analytical tools for business teams.
• Explore opportunities for
  data monetization
  through insights-as-a-service and ecosystem partnerships.
• Implement
  Responsible AI principles
  , ensuring fairness, explainability, and transparency across models.

The incumbent
must have
the following:

• Minimum of 4-year tertiary degree in Computer Science, Mathematics, Statistics, Data Science or related field
• Master's Degree in a Data Science, AI/ML, Statistical or related field (preferred)
• MBA or Masters (advantageous)
• 5 or more years of relevant work experience as a Data Engineer/ Data Scientist
• 4–6 years applied data science; 2+ years owning production AI/ML.
• At least 3 years' experience within a non-traditional FinTech, Banking or Financial Services Sector
• Experience in Data Science and Data Analysis with a specific focus on AI/ ML models within banking, finance and/or telecommunications industry
• Proven delivery of automated decisioning (recommendation/propensity/fraud/forecasting) with quantified business impact.
• Experience in Data Engineering within banking or financial services industry
• Understanding of enterprise-scale systems and technologies used in data infrastructures
• Experience of working in an Agile/DevOps environment
• GitHub or GitLab experience for CI/CD
• Consistent improvement CI/CD applications for collaborations and enhancement to drive develop once and deploy to many mindset through container repositories
• Proficiency in working with Python and its relevant libraries SAS or R / Scala for data clean up and advanced data analytics
• Working knowledge in Hadoop, Apache Spark and related Big Data technologies (MapReduce, PIG, HIVE)
• Demonstrated experience utilizing software tools to query and report data and being software agnostic
• Highly proficient in database management systems like Postgres, Oracle, Mongo, MSSQL
• Experience in data analysis and management, business performance management and/or reporting within the financial sector or banking industry

Ready to make and drive the change with us? Apply now

Closing date: 15 October 2025. Late applications will not be accepted.

Should you not hear from us within 2 weeks of applying, please consider your application unsuccessful.