Manager - Data Science.Fintech Commercial Operations at MTN

Responsibilities

Operational Delivery

• Data Mart Development and Maintenance:
• Design and maintain data marts to support analytics, reporting, and mathematical algorithms.
• Extract, transform, and load (ETL) data from various sources into structured formats suitable for analysis.
• Ensure data integrity, accuracy.

Data Science Capabilities:

• Stay abreast of the latest industry standards for Data Science tools & technologies.
• Translate identified business problems into data related or mathematical solutions. Identify what methods (e.g., analytics, big data analytics, or automation) will solve the problem.
• Analyse business problems with one’s discipline and question assumptions to help the business identify root cause.
• Make use of statistical methods, mathematical algorithms and tools & technology to “slice and dice” data and provide meaningful results to the business.
• Build algorithms and design experiments to merge, manage, interrogate and extract data to supply tailored reports as required.
• Machine Learning Operations Pipeline deployment

Data Governance and Quality Assurance:

• Implement data quality checks and validation processes to ensure high-quality datasets for analysis.
• Collaborate with IT and data governance teams to maintain compliance with data privacy and security standards.

Reporting and Visualization:

• Extract meaning from and interpret large sets of structured and unstructured data to deliver high quality reporting frameworks for business consumption.
• Develop interactive dashboards and reports to provide actionable insights to stakeholders at all levels of the organization.
• Collaborate with cross-functional teams to understand reporting requirements and deliver insights that drive informed decision-making.

Automation and Optimization:

• Ensure all data workflows and reporting processes are automated to improve efficiency.
• Optimize existing data pipelines and analytics processes to enhance performance and scalability.

Qualifications

Education:

• Bachelor's degree in Mathematics, Computer Science, Statistics, Data Science, Business Analytics, Actuarial Science, Business Mathematics, Informatics, Engineering or related.
• Evidence of participation in Machine learning competitions (Description of the problem and solution strategy).

Experience:

• Proven experience (5+ years) in Advanced Data & Analytics and Data Science.
• Big Data On-premise and Cloud Data Pipeline (M. Fabric) deployment
• Machine Learning Operations Pipeline deployment
• Web Open-Source Interface development
• API Development and Deployment
• Strong technical skills in data manipulation, analysis, and visualization tools such as SQL, Python, R, Tableau, or Power BI.
• Knowledge of database systems (e.g., Oracle, Teradata, or Snowflake) and cloud data platforms (e.g., AWS, Azure, or GCP).
• Excellent communication and stakeholder management skills, with the ability to translate technical concepts into actionable insights for non-technical audiences.
• Experience in the telecommunications/ Financial Services or Fintech Companies or related fields is a plus.

Apply Before 11/27/2025