Job Description

Tactical Implementation

• Work closely with your business to identify issues and use data to propose solutions for effective decision making
• Build algorithms and design experiments to merge, manage, interrogate and extract data to supply tailored reports to colleagues, customers or the wider organisation
• Use analytical tools and statistical techniques to produce solutions to problems
• Test data mining models to select the most appropriate ones for use on a project
• Maintain clear and coherent communication, both verbal and written, to understand data needs and report results
• Create clear reports that tell compelling stories about how customers or clients work with the business
• Assess the effectiveness of data sources and data-gathering techniques and improve data collection methods
• Horizon scan to stay up to date with the latest technology, techniques and methods
• Conduct research from which youll develop prototypes and proof of concepts
• Look for opportunities to use insights/datasets/code/models across other functions in the organisation (for example in the HR and marketing departments)

Data Modelling

• Research and develop custom data models and algorithms to apply to data sets
• Design data science approach, applying tried-and-true techniques or developing custom algorithms as needed by the business problem
• Lead multiple analytic project teams by serving as the senior technical thought leader for project teams; working with various business units to translate project goals into data analytic model
• Build predictive and data mining models with high dimensional and dynamic data and conduct analysis through the product & customer life cycle
• Effectively communicate and interpret model results for business
• Assist with developing the information roadmap, sourcing of new data sets and phasing of core reference data sets

Data Analysis

• Utilise Big Data analytics and advanced data mining techniques to analyse data and extract meaningful business insights and the story behind the pattern.
• Code, test and maintain analytical software tools
• Investigate adversarial trends, identify behavior patterns, and respond with agile logic change
• Perform analytical tasks such as text mining and sentiment analysis using Big Data techniques and algorithms.
• Analyse data from company databases to drive optimisation and improvement of MTN SA’s data quality and compliance
• Provide on-going tracking and monitoring of performance of decision systems and statistical models
• Communicate results of analysis to business partners/stakeholders and executives.

Continuous Improvement

• Develop usage and access control policies and systems in collaboration with the SM: Data Governance (Stewardship)
• Partner with the other data scientists in continuous improvement processes impacting data quality in the context of the specific use case
• Provide recommendations regarding campaign consolidation, integration, automation and optimisation based upon jobs requests worked upon
• Recommend ongoing improvements to methods and algorithms that lead to findings, including new information
• Engage with business teams to find opportunities, understand requirements, and translate those requirements into technical solutions

Collaboration / Coordination

• Collaborate with other functions across the business to ensure effectiveness of analysis conducted
• Collaborate with other functions to drive and where applicable enhance the utilisation of models, algorithms and software that help solve business problems
• Collaborate with data engineers and platform architects to implement robust production real-time and batch decisioning solution
• Interacting with the team members within the departments through the Customer lifecycle management and Product Performance to deliver on the Business priorities
• Understand campaigns that introduced to market to deliver on the Business priorities

Reporting

• Review and submit reports addressing periodic activity, budget compliance, feedback and key departmental results to facilitate decision making
• Track and report on model performance deployed in production – outcome of the model and change in behaviour regarding customer and product life cycle.
• Prepare reports on operational performance and detailed reports on specific channel sales performance and campaigns when required
• Communicate to business units the various predictions and findings through effective data visualisations and reports

Responsibilities

Tactical Implementation

• Work closely with your business to identify issues and use data to propose solutions for effective decision making
• Build algorithms and design experiments to merge, manage, interrogate and extract data to supply tailored reports to colleagues, customers or the wider organisation
• Use analytical tools and statistical techniques to produce solutions to problems
• Test data mining models to select the most appropriate ones for use on a project
• Maintain clear and coherent communication, both verbal and written, to understand data needs and report results
• Create clear reports that tell compelling stories about how customers or clients work with the business
• Assess the effectiveness of data sources and data-gathering techniques and improve data collection methods
• Horizon scan to stay up to date with the latest technology, techniques and methods
• Conduct research from which youll develop prototypes and proof of concepts
• Look for opportunities to use insights/datasets/code/models across other functions in the organisation (for example in the HR and marketing departments)

Data Modelling

• Research and develop custom data models and algorithms to apply to data sets
• Design data science approach, applying tried-and-true techniques or developing custom algorithms as needed by the business problem
• Lead multiple analytic project teams by serving as the senior technical thought leader for project teams; working with various business units to translate project goals into data analytic model
• Build predictive and data mining models with high dimensional and dynamic data and conduct analysis through the product & customer life cycle
• Effectively communicate and interpret model results for business
• Assist with developing the information roadmap, sourcing of new data sets and phasing of core reference data sets

Data Analysis

• Utilise Big Data analytics and advanced data mining techniques to analyse data and extract meaningful business insights and the story behind the pattern.
• Code, test and maintain analytical software tools
• Investigate adversarial trends, identify behavior patterns, and respond with agile logic change
• Perform analytical tasks such as text mining and sentiment analysis using Big Data techniques and algorithms.
• Analyse data from company databases to drive optimisation and improvement of MTN SA’s data quality and compliance
• Provide on-going tracking and monitoring of performance of decision systems and statistical models
• Communicate results of analysis to business partners/stakeholders and executives.

Continuous Improvement

• Develop usage and access control policies and systems in collaboration with the SM: Data Governance (Stewardship)
• Partner with the other data scientists in continuous improvement processes impacting data quality in the context of the specific use case
• Provide recommendations regarding campaign consolidation, integration, automation and optimisation based upon jobs requests worked upon
• Recommend ongoing improvements to methods and algorithms that lead to findings, including new information
• Engage with business teams to find opportunities, understand requirements, and translate those requirements into technical solutions

Collaboration / Coordination

• Collaborate with other functions across the business to ensure effectiveness of analysis conducted
• Collaborate with other functions to drive and where applicable enhance the utilisation of models, algorithms and software that help solve business problems
• Collaborate with data engineers and platform architects to implement robust production real-time and batch decisioning solution
• Interacting with the team members within the departments through the Customer lifecycle management and Product Performance to deliver on the Business priorities
• Understand campaigns that introduced to market to deliver on the Business priorities

Reporting

• Review and submit reports addressing periodic activity, budget compliance, feedback and key departmental results to facilitate decision making
• Track and report on model performance deployed in production – outcome of the model and change in behaviour regarding customer and product life cycle.
• Prepare reports on operational performance and detailed reports on specific channel sales performance and campaigns when required
• Communicate to business units the various predictions and findings through effective data visualisations and reports

Qualifications

• Minimum of 3-year tertiary degree in (STEM); Computer Science, Mathematics, Statistics, Finance or related quantitative field

Required Skills

• Data base modelling and data warehousing principles (SQL)Data science and advanced analyticsStrong Programming skills (R, SAS, Python, C++, Java