MIS and Data Science Manager at Vodafone Ghana

Job Description
The MIS & Data Science Manager:

•     Supervise the operational drive to ensure that the D&A team meets its objectives in an effective and efficient manner.
•     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.
•     Supervise the delivery of accurate, insightful, and timely analysis into the performance of the business.
•     Employs the innovative use of technology to automate and improve the quality, relevance, and timely generation of reports and dashboards.
•     The position will focus on establishing and ensuring adherence to an enterprise data governance framework for data policies, standards and practices, both at the department and Business and Functional areas level, to achieve the required level of consistency, quality and protection to meet overall business needs.
•     Drive continuous improvement to create efficiencies in service delivery.

Job Responsibility

•     Supervise the dissemination of financial information on business performance to key stakeholders including, but not limited to, Management, Commercial Performance teams, Regulators and External Auditors.
•     Lead cross-functional projects using advanced data modelling and analysis techniques to discover insights that will guide strategic decisions and uncover optimization opportunities.
•     Oversee the design and delivery of reports and insights that analyse business functions and key operations and performance metrics using available BI tools and ensure all reporting timelines are met.
•     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 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
•     Propose solutions and strategies to business challenges and lead the documentation and maintenance of business reporting definitions.
•     Serve as a liaison between Business and Functional areas and technology to ensure that data related business requirements for protecting sensitive data are clearly defined, communicated and well understood and considered as part of operational prioritization and planning•    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
•     Roll out an enterprise-wide data governance framework, with a focus on improvement of data quality and the protection of sensitive data through modifications to organization behaviour policies and standards, principles, governance metrics, processes, related tools and data architecture    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
• 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)