Manager - Data Analytics.Remittance And Fintech Business Development at MTN

Job Description

• The role of the Manager: Data Analytics is to automate date pipeline,structure datasets, leverage internal and, where applicable, external datasets to build and evolve, Group Fintech’s Services & Product capabilities using “best practice” methodologies and statistical techniques.
• Responsible to structure the datasets at both OPCO & Group level, to design and provide insights based on analytics, to structure & deliver through OPCOs the necessary reporting, to develop decision models & data-based rules in support of the strategy & plans of the product portfolio.

Responsibilities

• Support Fintech Analytics strategy execution in line with the overarching business and functional goals
• Provide reports and analysis to support and contribute to the development of the functional strategy in line with the overarching business goals
• Support the execution and development of data mining and analysis frameworks 
• Ensure accurate and timely reporting to enable the regular review of the functional strategy, roadmap and performance to ensure its alignment with the changing dynamics of the internal and external ecosystem
• Drive analytics & reporting roadmap forbusiness ; prioritize business insight requests to balance the tactical and strategic information needs
• Develop and manage models to ensure business and customer growth
• Develop and Manage models in the areas of machine learning and data sciences in building the various components of the semantics layer
• Develop advanced quantitative modules using a variety of programs/software to support predictive assessment
• Develop automated processes for data ingestion, transformation and visualisation
• Develop BI content - reports, dashboards, scorecards, analytic solutions supporting effective business decisions and measurement of goals and overall performance of Fintech portfolio
• Perform complex analyses, including optimization, text analytics, machine learning, social-science modeling, and statistical analysis, parametric and non-parametric statistical models and techniques
• Collate business intelligence data through public information, industry and field reports, or purchased sources, to provide outside in view to the business teams
• Establish intuitive reporting methodologies, perform ad-hoc market analysis as required to support the functional strategy and analyze performance
• Work with Technology teams on the development of new data capabilities & architecture to define requirements and priorities
• Develop, continuously improve, & execute an efficient framework to identify, organize, structure, make available data attributes and information relevant for digital advertising 
• Define & continuously optimize targeting approaches for Remittance Products & Services
• Develop predictive models to forecast remittance volumes, transaction patterns, and currency exchange rates
• Support in the implementation & use machine learning techniques to enhance fraud detection and risk management strategies 
• Monitor transaction data to ensure compliance with regulatory requirements and feedback to risk & compliance for development of mitigation strategies

Qualifications

Education

• 4-year Business Mathematics, Statistics, Data Science (or related) Degree
• Master’s in business administration is advantageous

Experience

• A minimum of 5 years’ experience in financial services, consulting, strategy, analytics, engineering, or related industry
• 2 - 3 years of experience in data structuration, data management, analytics, big data, and a similar environment
• Minimum of 1 -2 years’ experience in an area of Data Science, at a specialist level within the financial /banking industry or telecommunications industry
• Experience working in a medium to large organization 
• Experience of working in an Agile/DevOps environment
• Proficiency in working with Python (Numpy, Scikit-learn, Pandas, Scipy, Matplotlib, Tensorflow, Keras, Seaborn, Bokeh), 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: SAS (Enterprise Guide and/or programming), tableau, Power BI,D3 VBA, SQL, and Business Objects
• Highly proficient in database management systems like Postgres, Oracle, Mongo, MSSQL

Apply Before 03/30/2026