Job Description
Job Title: MIS & Data Science Mgr
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 carry 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 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
- 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 are 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)