MIS & Data Science Manager - Vodafone Ghana

The MIS & Data Science Analyst:

• Enhancing data collection procedures to include all relevant information for developing analytic systems
• Using machine learning tools to select features, create and optimize classifiers and carrying out pre-processing of structured and unstructured data
• Employs the innovative use of technology to automate and improve the quality, relevance, and timely generation of reports and dashboards
• Drive continuous improvement to create efficiencies in service delivery

Job Responsibility

• Support the dissemination of financial information on business performance to key stakeholders including, but not limited to, Management, Commercial Performance teams, Regulators and External Auditors
• Participate in advanced data modelling and analysis techniques to discover insights that will guide strategic decisions and uncover optimization opportunities
• Deliver reports and insights that analyse business functions and key operations and performance metrics using available BI tools and ensure all reporting timelines are met
• 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 finance decision support team (CBU & EBU) to make informed decisions on new product development and portfolio rationalization and ensure a high level of data quality for all reporting and analysis
• 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
• Collaborate with the finance decision support team (Technology) to generate actionable insights on cell site profitability and track regional performance
• Develop & maintain inventory of the enterprise information maps, including authoritative systems, owners
• Facilitate the development and implementation of data quality standards, data protection standards and adoption requirements across the enterprise
• Data mining or extracting usable data from valuable data sources and processing, cleansing, and validating the integrity of data to be used for analysis
• Analysing large amounts of information to find patterns and solutions and Developing prediction systems and machine learning algorithms
• Presenting results in a clear manner and propose solutions and strategies to tackle business challenges whiles collaborating closely with Business and IT teams

Core competencies, knowledge, and experience

Leadership 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
• Train end-users on the use of data and analytics software or tools

Drive

• Must be able to plough through challenges and see all tasks to their conclusion
• Constructively challenge and assist CVM, 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
• Understanding of machine-learning and data mining technologies. Good knowledge of machine learning methods like k-Nearest Neighbours, Naive Bayes, SVM, Decision Forests
• Knowledge of R, SQL, and Python
• Experience using business intelligence tools (e.g. Tableau)
• An understanding of budgeting procedures, methods and evaluation criteria
• Strong Math Skills (Multivariable Calculus and Linear Algebra) – understanding the fundamentals of Multivariable Calculus and Linear Algebra is important as the basis for predictive performance or algorithm optimization techniques

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)

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