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14 Apr 2023

Analyst – Segmentation and Propensity Model at MTN

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Job Description


Reports to: Senior Manager – Customer Value Management and Loyalty

Main Job Functions:
Strategy
• Enable the customer base management strategy and campaign roadmap by developing predictive models and segmentation which supports the overall CVM strategy and P&L by increasing offer relevance and revenue uplift.
• Operationally manage these models to deliver commercial return and technical implementation to allow automation.

Delivery
• Create and maintain model development roadmap.
• Business case development to determine the commercial opportunity of implementing models.
• Automation of developed models
• Integration of models in campaign management and customer interfacing support systems
• Delivery, implementation, and enhancement of a CVM specific deal creation program (Next best action)
• Managing machine learning predictive models and their outcomes
• Enhancing modelling capability by evaluating technical modelling platforms

Capability
• Create and maintain model development roadmap including the technical requirements for big data inclusion in the analytical environment.
• Ability and expertise in building statistical data models, predictive analytics, segmentation and clustering, heuristic analytics, exploratory analytics.
• Integration of models in key campaign management systems
• Enhancing modelling capability by evaluating technical modelling platforms
• Prior experience in conducting and designing internal and external research.
• Proficiency in analytics tools like SAS/UNICA/Power BI, etc

Supervisor / Leadership / Managerial Tasks:
• Have the self-insight and flexibility to adapt to different situations.
• Communicate actively and effectively resolving any potential conflicts that may arise.
• Employee relations and collaborative teamwork
• Manage contributions and expectations of external service providers and stakeholders.
• Ensure ongoing liaison with other areas of the business.
• Review performance management, evaluating, assessing, and tracking performance to ensure that objectives and targets are achieved.
• Build and enforce a customer centric approach.
• Live the MTN Brand values –influence employees’ behavior.
• Influence other stakeholders to achieve the business objectives of the channel

Education:
• Bachelor’s degree preferably in mathematics, Economics, Information Technology, Statistics, Business computing or Commerce
• Postgraduate qualification in Marketing or Business Administration

Experience:
• At least 3 years’ experience in business analysis and financial modeling in the marketing environment.
• Demonstrated leadership in predictive modelling within a large organization.
• Experience in predictive model development, maintenance, commercialization, and automation.
• Commercially astute
• Experience in managing dynamic learning engine solutions (preferred)
• Experience with technical and commercial implementation of predictive models
• Telecommunication experience is an added advantage.
• Highly proficient in all MS Office applications: Word, Excel, PowerPoint, and database experience
• Demonstrated ability to create structure within an unstructured environment.
• Disciplined detail-oriented style, combined with ability to simultaneously work at a strategic level

Knowledge, Skills and Competencies:
• Expertise in customer data, information systems, data warehouses, data marts, business intelligence software and systems
• CVM methodology, principles, capabilities, and techniques.
• Business Analysis and Data Management
• Statistical modeling and multivariate analysis
• Segmentation techniques
• Scoring techniques
• Data Quality analysis
• Algorithm Knowledge
• Data mining and predictive analytics
• Reporting and performance analysis
• Knowledge of local markets, including market trends
• Business Performance Measurement & Management
• Business and financial planning

Female applicants are strongly encouraged to apply.

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Method of Application

Submit your CV and Application on Company Website : Click Here

Closing Date : 28th April, 2023




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