Specialist: Product Analytics & Insights

About

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 Specialist: Product Analytics & Insights, you will be:

• The Specialist: Product Analytics & Insights is responsible for supporting the Payments & E-Commerce Products team through business-focused analytics, reporting, data validation, and insight generation.
• The role ensures that product, commercial, and operational decisions are informed by accurate, timely, and relevant data drawn from multiple internal and external platforms.
• The role is accountable for extracting, preparing, validating, analysing, and interpreting data for business reporting and decision support across payments and e-commerce products. This includes loading and reconciling data, monitoring data quality, supporting KPI reporting, identifying trends and anomalies, and generating actionable insights that improve product performance, customer engagement, and commercial outcomes.
• Acts as a business analytics specialist embedded within the Payments & E-Commerce Products team, focused on using available data to support reporting, performance management, and business decision-making.
• This is an individual contributor role requiring strong analytical capability, curiosity, business understanding, and the ability to convert data into meaningful commercial insight.

Operational Delivery

Business Reporting and Insights

• Prepare, maintain, and enhance regular business reports, dashboards, and performance packs for the Payments & E-Commerce Products team.
• Support reporting on key business metrics including volumes, values, customer activity, product usage, revenue trends, conversion metrics, and channel performance.
• Analyse data from multiple platforms and sources to identify trends, performance drivers, operational issues, and growth opportunities.
• Translate raw data into meaningful business insights and management information for product and commercial teams.
• Provide ad hoc analysis to support business reviews, product decisions, campaign assessments, and leadership requests.

Data Validation and Quality Assurance

• Load, reconcile, and validate data received from various platforms and business sources before use in reporting and analysis.
• Perform data quality checks to ensure completeness, consistency, timeliness, and accuracy of reported data.
• Investigate data discrepancies, anomalies, and exceptions, and work with relevant teams to resolve data quality issues.
• Support the creation of controls and validation routines that improve confidence in business reporting outputs.
• Maintain documentation of data definitions, assumptions, validation logic, and reporting methodologies.

Product and Commercial Analytics

• Support product managers and business teams with analytics on product performance, customer behaviour, transaction trends, and market performance.
• Analyse usage patterns across payments and e-commerce products to identify opportunities for optimisation, adoption growth, and customer value creation.
• Generate insights that support product enhancements, go-to-market decisions, and commercial prioritisation.
• Support analysis of new initiatives, pilots, and product launches by tracking performance against business objectives and expected outcomes.
• Contribute to business case development through relevant data analysis and scenario inputs.

Data Preparation and Analytical Support

• Extract, clean, transform, and prepare datasets for analysis and reporting using available tools and business data sources.
• Support automation of recurring reporting and analytical workflows to improve efficiency and reduce manual effort.
• Assist in integrating data from spreadsheets, reports, APIs, and business systems into fit-for-purpose analytics outputs.
• Maintain structured datasets, templates, and trackers used by the Payments & E-Commerce team for ongoing reporting and performance reviews.

Stakeholder Support and Collaboration

• Work closely with Product, Commercial, Finance, Technology, and Reporting teams to understand business questions and respond with relevant data analysis.
• Liaise with the central Data Engineering & Governance team where required to clarify source data structures, definitions, or dependencies.
• Support a data-driven decision-making culture by making reporting and insights accessible, practical, and business-relevant.
• Participate in business reviews and analytics discussions to explain trends, assumptions, and findings clearly to non-technical stakeholders.

Requirements

Education:

• Bachelor of Science, Computer Science, Big Data, Database Administration or related fields.
• Evidence of strong skills in Data pipeline building.

Experiences:

• Proven experience (3+ years) in Advanced Data Engineering.
• API Development and Deployment
• Strong technical skills in data manipulation and analysis tools such as SQL, Python, R.
• Knowledge of database systems (e.g., Oracle, MS SQL) and cloud data platforms (e.g., AWS, Azure, or GCP).
• Experience in the telecommunications/ Financial Services or Fintech Companies or related fields is a plus.
• Demonstrated ability to collaborate effectively with cross-functional teams and external partners to achieve business objectives.
• Excellent written and verbal communication skills. Understanding emerging markets

What will give an edge to your application:

Functional Knowledge

• Business reporting and performance analytics
• Product and commercial analytics
• KPI development and dashboard reporting
• Data quality validation and reconciliation
• Business insight generation and trend analysis
• Data preparation and analytical dataset management
• Payments and e-commerce product environments
• Understanding of digital customer and transaction data

Skills

• Analytical thinking and interpretation
• SQL and data querying
• Dashboarding and business visualization
• Data validation and reconciliation
• Business storytelling with data
• Problem solving
• Stakeholder engagement
• Continuous improvement
• Digital mindset
• Attention to detail