The Performance Analytics and Insight Manager:

• Using machine learning tools to select features, create and optimize classifiers and carrying out pre-processing of structured and unstructured data
• Supervise the delivery of accurate, insightful, and timely analysis into the performance of the business
• Weekly business rolling forecast inputs and actuals tracking
• Employs the innovative use of technology to automate and improve the quality, relevance, and timely generation of reports and dashboards
• Demand management
• Provide automated reports & visualizations for financial and non-financial reporting
• Support in Internal Management data & reports
• Support in the data analytics for budgeting and planning
• Work closely with the Finance Business Partners and Commercial Analyst for all their data requirements
• Drive continuous improvement to create efficiencies in service delivery

Job Responsibility
Key accountabilities and decision ownership:

• Supervise the delivery of accurate, insightful, and timely analysis into the performance of the business
• Lead projects using advanced data modelling and analysis techniques to discover insights that will guide strategic decisions and uncover optimization opportunities
• Work closely with the Finance Business Partners and Commercial Analyst for all their data requirements
• Lead and manage all organization-wide data governance activities and will have responsibility for improving the quality and managing the protection of sensitive data and information assets
• Provide analytics and insights to the business on consumer behaviour /usage and the impact of network performance on service revenue and prepare all business forecast
• Provide data and insights to the commercial business units and finance decision support teams to aid in conducting post-implementation reviews on newly launched products
• Propose solutions and strategies to business challenges and lead the documentation and maintenance of business reporting definitions
• Data mining or extracting usable data from valuable data sources and processing, cleansing, and validating the integrity of data to be used for analysis
• Analyzing large amounts of information to find patterns and solutions and Developing prediction systems and machine learning algorithms

Core competencies, knowledge, and experienceLeadership and teamwork

• Must be able to work effortlessly within the team and across the business to drive discussions on business performance
• Must show initiative and anticipate the needs of the team and work proactively to deliver the necessary support

Innovation and change

• Must have a natural inclination for seeking out new ideas and opportunities
• Should exhibit creativity in approaching everyday challenges in the workplace
• Design, automate and disseminate interactive business reports to generate actionable insights

Drive

• Must be able to plough through challenges and see all tasks to their conclusion
• Constructively challenge and assist EVM and the new Product development teams with data and insights to manage customer base, reduce churn and develop exciting products

Technical Competence

• Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators, etc. Proficiency in statistics is essential for data-driven decision making
• Must have strong analytical, conceptual, and problem-solving abilities
• Must possess excellent attention to detail
• Proven experience using excel
• Experience using business intelligence tools (e.g. Tableau)
• An understanding of budgeting procedures, methods and evaluation criteria

Communication

• Must be able to communicate confidently both orally and in writing. Presentations to the business is a normal requirement for this role
• Must have good interpersonal skills to support working closely with the Financial teams within the business

Must have technical / professional qualifications:

• A Bachelor’s degree in Accounting, Finance, Engineering, Computer Science or Mathematics/Statistics, Actuarial Science
• Prior experience in the telecoms industry (an advantage but not required)
• Knowledge in AI/ML, SAP, HFM, SQL, Python, R , Power BI, Tableau and other relevant system software
• Knowledge of revenue streams within the telecoms industry (an advantage but not a requirement)