Senior Manager - Data Analytics at MTN

Responsibilities

Key Performance Areas

• Models and frames business scenarios that are meaningful and which impact on critical business processes and/or decisions, across descriptive, predictive, and prescriptive analysis.
• Provide solutions to defined business problems by leveraging pattern detection over potentially large datasets.
• Identifies what data is available and relevant, including internal and external data sources, leveraging new data collection processes such as smart meters and geo-location information or social media, ability to work with structured/unstructured/semi structured data.
• Collaborates with subject matter experts to select the relevant sources of information & translates the business requirements into a data mining project. Adept at breaking down a project into its constituent phases
• Proficiency in statistical analysis, quantitative analytics, forecasting/predictive analytics, multivariate testing, and optimization algorithms.
• Utilizes patterns and variations in the volume, speed and other characteristics of data supporting the initiative across a range of data formats (e.g., images, text, clickstream or metering data)
• Makes strategic recommendations on data collection, integration and retention requirements incorporating business requirements and knowledge of best practices.
• Develops content for and educates the organization both from IT and the business perspectives on new approaches, such as testing hypotheses and statistical validation of results. Helps the organization understand the principles and the math behind the process to drive organizational buy-in
• Defines the validity of the information, how long the information is meaningful, and what other information it is related to.
• Design, development, and validation of descriptive, predictive, prescriptive, and applied Analytics
• Proficiency in using query languages such as SQL, Hive, Pig Experience with NoSQL databases, such as MongoDB, Cassandra, HBase 
• The role works closely with clients, data stewards, project/program managers, and other IT teams to turn data into critical information and knowledge that can be used to make sound organizational decisions or otherwise operationalized in real-time to deliver bottom line business results. 
• Validate findings using an experimental and iterative approach. 
• Present findings to the business by exposing their assumptions and validation work in a way that can be easily understood by their business counterparts.

Qualifications

Education:

• 4 years Bachelor’s degree in mathematics, statistics, computer science or related field
• Post-graduate degree in Data Analytics, engineering, or related technical area of study is strongly preferred
• Understanding of the Telecom domain and its main data sources is highly advantageous

Experience:

• 4 - 8 years of relevant work experience in a global / multinational business environment (understanding of emerging markets advantageous)
• Minimum of 3 years of data analytics experience as a Data Scientist or Data Architect
• Deep knowledge and experience in data analytics tools (SQL, Python, SAS, etc.)
• Deep knowledge and experience in data reporting/visualisation tools (Power BI, Tableau, etc.)
• High proficiency in machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
• Experience with common data science toolkits, such as SAS, R, SPSS, etc Strong proficiency in at least one of these is required
• Experience with data visualization tools, such as Power BI, Tableau, etc.

Competencies:

• Managing technology and commercial personnel
• Business focus, strong analytical and problem-solving skills and deep programming expertise to be able to quickly cycle hypothesis through the discovery phase of the project.
• Proficient communication skills & the ability to take complex outputs and present back to business owners