Manager Data Scientist MTN Vacancy

Reference Number:
MTNVAC-206

Title:
Manager Data Scientist

Location:
Roodepoort, ZA

Organisation Name:
Group Strategy

Department:
Group Strategy

MTN Level:
Level 3

Mission/ Core purpose of the Job

The Data Scientist role is responsible for modelling complex business problems, discovering insights and identifying opportunities using statistical, algorithmic, Machine Learning/Mining and visualization techniques. In addition to advanced analytic skills, this person needs to be proficient at integrating and preparing large, varied datasets and communicating results.

Context (Global influences, environmental / industry demands, organisational mission etc.)

ExCo has mandated the establishment of a Business Intelligence Competency Centre to evolve BI practices to better serve MTN. The vision of the BICC is to create a permanent core BI organization in Group (BICC), staffed with highly skilled full-time professionals from across the enterprise. This unit will work with Tech BI and BICC teams in OpCos to leverage Group’s BI capabilities and technology in support of the strategic initiatives of the business. In doing so, the BICC aims to achieve the following:

Standardise BI across MTN
Enable each OpCo to provide BI competency suited to their needs
Agility and efficiency in all BI-related activities
Suitability and relevance of MTN-developed BI solutions, in Group and OpCos

Key Performance Areas: Core, essential responsibilities / outputs of the position (KPA’s)

Models and frames business scenarios that are meaningful and which impact on critical business processes and/or decisions
The ability to come up with 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, the type of data (e.g., images, text, clickstream or metering data) in predictive analysis
Makes strategic recommendations on data collection, integration and retention requirements incorporating business requirements and knowledge of best practices.
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.
Excellent understanding of 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 Excellence in at least one of these is highly desirable
Experience with data visualization tools, such as Power BI, Tableau, etc.
Proficiency in using query languages such as SQL, Hive, Pig Experience with NoSQL databases, such as MongoDB, Cassandra, HBase
Proficient communication skills & the ability to take complex outputs and present back to business owners

Job Requirements

Job Requirements (Education, Experience and Competencies)

Education:

4 years Bachelor’s degree in mathematics, statistics or computer science or related field
Post-graduate degree in a related analytic/engineering field is a plus

Experience:

Minimum of 2 years of relevant work experience as a Data Scientist or Data Analyst, with experience building complex analytical models leveraging structured and/or unstructured data
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
Competencies:
Logical Modelling
Telecommunications Industry
Influencing others
Information processing
Problem solving
Risk management
Analytics, Big Data
Communication Skills (Verbal, Written)
Analytical
Continuous improvement
Data interpretation
Judgment
Reporting
Managing technology and commercial personnel
The data scientist must be highly skilled in the design, development, and validation of descriptive, predictive, prescriptive, and applied Analytics

Apply Now