Data Scientist

The Foschini Group

Parow (Parow)

1d ago

Position Description : A demanding and challenging opportunity has arisen within the Customer Data Hub Department of TFG for a dynamic, highly motivated individual to provide analytical solutions that will improve decision making throughout the customer life cycleJob description

The development and deployment of a suite of response, propensity and segmentation models to improve customer targeting capability for acquisition, cross-selling, retention and customer management initiatives across all retail brands, financial products and delivery channels

Analysing customer behavioural patterns and proposed customer relationship journeys to improve profitability and provide actionable insights for broader business strategy

The development and deployment of predictive models and analytical strategies to improve decision making throughout the customer life cycle of the TFG account base, from acquisition and new account decision to existing customer management

Data mining of credit bureau and other external data to provide insights and trends

The development of variable / characteristics from external data to improve credit management decisions and accuracy of predictive models

Ensuring appropriate statistical methodology and data mining / analytical techniques are applied to modelling process to deliver and deploy robust and effective models

Forecasting models / time series analysis to examine portfolio trends and to provide strategic tools as input into business projections

Providing analytical solutions to complex business problems

Extraction and preparation of data for internal development projects as well as outsourced solutions

Model tracking to ensure effective model life cycle management and recommendations for redevelopment

Effective communication and presentation of analytical results to different stakeholders

Conducting peer-on-peer quality assurance to ensure consistency in delivery

Documentation of analytical processes and results, adhering to agreed documentation standardsTo take up this challenging position you should have :

A degree in a numerate discipline, preferably Statistics / Mathematics / Operations Research (Honours / Master’s degree preferable)

Experience in predictive modelling or scorecard development and of solving complex business, data, and technology problems through leveraging Data and Analytics solution options.

Experience and knowledge of data engineering tools in AWS and / or Azure as well as analytics tools such as SAS, SAS Enterprise Miner, R, Python, SPSS, MATLAB and BI tools such as QlikView, Power BI, Tableau is required for technical domains, while experience in MDM, metadata, and data quality toolsets or platforms would be advantageous

Knowledge of the credit industry and credit life cycle management

Hands-on experience of large-scale customer database data interrogation and manipulation

Experience with data mining and statistical techniques such as logistic regression, decision trees, cluster analysis etc.

Excellent data interpretation skills

A customer centric approach

Good strategic and conceptual abilities

Advanced problem solving, judgement and self-management skills

Design and development of corporate performance managing assets like KPI, scorecards and dashboards

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