Vodafone
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)