Specialist - Data Scientist Fintech CEO's Office at MTN

Job Description
Mission/ Core purpose of the Job:  

• To deliver analytics and insight within the digital services organization to support MFS. 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

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