Manager – Senior Data Scientist Consumer at MTN

Mission/ Core purpose of the Job:

To deliver analytics and insight within the Consumer CVM organization to support MTN Digital Strategies. Assist in solving business problems and exploit untapped opportunities using AI, machine learning and deep-learning through the development of models, algorithms and software. Be the data subject matter expert on the services within the digital domain

RESPONSIBILITIES
Context:

Highly dynamic and fluctuating telecommunications industry
Positioning of MTN as leading telecommunications player in the market
Within the dynamic legal, regulatory and commercial environment of South Africa
Highly competitive market with new and established competitors
Fast moving industry
Context changes in terms of technology advancements
Legislative changes
Ongoing technology advancements
Changes in consumer behaviour
Work within the data warehousing and datamart environments
Dynamic technology environment
Highly specialized working environment
Complex and multiple data sources
Large volumes of Data
MTN system and Data architecture
MTN Data entity definitions
Fluctuating market trends and indicators
Broad product and service portfolio

Key Performance Areas:
Task Complexity:

Intelligence Measurements and Reporting
Research on customer buying and data usage patterns in order to have a holistic analysis
Assist with data extraction for customers from internal and external sources within the MTN SA market
Assist in data clean ups to information by ensuring that data is updated and pruned
Thoroughly scrutinize data in order to determine SWAT across all of MTN SA segments
Report on relevant performance metrics for the business objectives in line with Business objectives
Facilitate accurate data analysis and reporting of customer analytics and intelligence
Delivery of insightful market intelligence and insights to support business intelligence objectives utilising customer analytics
Interpret data and develop relevant recommendations based on data analysis findings
Develop graphs, reports and presentations of projects results
Perform basic statistical analysis for projects and reports
Data manipulation and modelling
Customer behavioural analysis
Predictive modelling and machine learning
Create and present quality dashboards
Generate standard monthly and ad hoc reports

Internal Processes and Efficiency

Prioritise requests and coordinate with IT to ensure availability, storage, sharing and certification of required information and data integrity
Support data and application design for the implementation of an automated customer analytics
Provide recommendations regarding campaign consolidation, integration, automation and optimisation based upon jobs requests worked upon
To provide more insights into the ways to target customers

Operational Planning and Management

Plan and coordinate the data extraction and reporting processes
Consider the long term (1-2 years) implications of action from a broader perspective
Consider local conditions, as well as competitor activity
Identify and exploit new opportunities to grow the business further
Identify innovative ways to use minimum resources to achieve maximum outputs

Advanced Analytics and Data Science:

Good understanding of all machine learning fundamentals
Enjoy coding in one of or all of R, SAS or Python (even with its weak definition of scope)
Work with both SQL and NoSQL databases
Work with Big-data stores such as Hadoop via Hive, Spark etc.
Implement deep-learning algorithms to solve real business problems
A complicated emotional response to both vanishing and exploding gradients
A data story teller, you are happy communicating your findings via dashboarding (Tableau, Power BI) or through presentation (Excel, PowerPoint)
Strong written and verbal communication skills

Strategic Input

Understand how business and IT requirements can be met using the correct blend of existing and new IT technologies.
Develop goals, strategies, and plans needed to achieve the portfolios vision and build the capabilities to enable optimal delivery with input from relevant stakeholders.
Support the enablement of a self-service philosophy
Create and implement the concepts and ideas for possible future implementation.
Assist with developing the information roadmap, sourcing of new data sets and phasing of core reference data sets

Supervisory / Leadership / Managerial Complexity:

Manage activities between internal MTN departments and resources.
Ensure accountability such that customer centricity culture is adhered to
Maintain good Employee relations and enhance collaborative teamwork
Mentorship, Coaching, Guidance and training to digital team
Build professionalism, loyalty and commitment to the organization

Role Complexity:

Interacting with the team members within the departments through the Customer lifecycle management and Product Performance to deliver on the Business priorities
Support the Digital team to deiver on Customer lifecycle and Product management business objectives
Understand campaigns that introduced to market
Data Manipulation and Modelling
Customer behavioural analysis
Predictive modelling
Statistical analysis
Use reports and Dashboards to analyse marketing data
Must be proficient in MS Office and Statistical Software Packages, e.g. SAS, SPSS, JMP, SQL, R

Lateral Dimensions:

Creativities (improvement/innovation inherent)
Effecting job request in a timely and efficient manner
Accurately extract data required and reporting on the findings
Provide unique and innovative ways of conducting data provisioning and reporting to users
Explore innovative ways to enhance the analytical and data supporting offerings
Establish sound relationships with all other business areas and stakeholders
Identify innovative ways to use minimum resources to achieve maximum outputs
Identify and exploit new opportunities to grow the business further
Apply market insights and intelligence in an optimal way to add as much value to relevant business arears
Speedy communication of results and recommendations to the relevant areas to enable the development of competitive advantage
Encourage continuous service improvement
Proactively seek information on business issues, particularly outside the Marketing Support unit which may impact on the unit
Motivate peers and reports through innovative interaction

Vulnerabilities (control span)

Limited resources
Unavailability and ineffective application of resources
Ineffective application / system support (SLA)
Reliance on the stability and availability of systems
Insufficient storage space to conduct data analysis exercises
Lack of data integrity
Evolution of technology
Fluctuations in the market
Competitive activity
Ineffective support from key stakeholders
Customer dissatisfaction
Non-achievement of turnaround times
Inappropriate processes resulting in delayed service to clients
Company project prioritisation
Unrealistic business expectation vs delivery
Continuous improvement of process and data integrity up-stream

Collaboration:
Responsibility towards:

Direct reports: None
Matrix reports: None
Key customers: MTN SA Executives, General Managers and Senior Managers with their functional areas
Key suppliers: Technology Team, Finance, Service Providers, Competitive Intelligence, Marketing Support Team
Relations, etc.: All departments in MTNSA and Group, MTN’s business strategy, MTN IS operations and applications, Network division, Enterprise business unit (EBU)

Discretionary Space:
Independent thought and Judgment:

Can set objectives for the unit
Dissemination of information
Implementation of systems, processes and policies to effectively analyse and provide data and evaluate effectiveness within business unit
Team motivation
Budget compliance
Resource allocation
System, process and procedure fine-tuning and development to achieve business objectives
Work with minimal restriction on boundaries of requirements (reporting, assignments, etc.)
Proactively identify opportunities for data/report provision to key stakeholders
Interpret, evaluate ad make recommendation based upon findings of trended information and outputs

Authorities:

As per delegation of authority

QUALIFICATIONS
Minimum Requirements:
Global Education Standards (10):

3 year Degree / Diploma in Commerce (Statistics, Mathematics, Computer Science, Engineering, Physics) or related
Fluent in English and one other official South African language

Global Experience Standards (10)

Minimum of 5 years’ experience in Commerce (Statistics, Mathematics, Computer Science, Engineering, Physics); with experience in supervising others 3+ years data science and machine learning experience
Experience working in a social media or digital service organisation
Experience in deep learning a major plus
Experience working in Telecommunications a major plus
Experience working in a Large organization

Training:

Data science
Advanced analytics
Data Visualisation (tools such as Power BI, Tableau etc.)
Products and Services and Solutions
Systems training
Computer software training
Project management
Communication and Negotiation skills
Assertiveness