Data Scientist

**Job ID**:16867**Position Type**:Full-Time**Job Function**:Marketing & Communications**Workplace Type**:
**Division**:TFG Customer Hub**Province**:Western Cape**Location**:Cape Town North**Suburb**:Parow (Parow)Position Description:
**Data Scientist (Analytics Specialist) - Customer and Loyalty**

**Cape Town**
**Permanent**

**The opportunity**:
A demanding and challenging opportunity has arisen within the Customer and Loyalty Department of TFG for a dynamic, highly motivated individual to provide Data Science and analytical solutions that will improve decision-making throughout the customer life cycle.

**Responsibilities**:

- 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 and reporting on customer behavioural patterns and proposed customer relationship journey 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 decisions to existing customer management.
- Data mining of external data to provide insights and trends.
- The development of variables/characteriics from external data to improve customer management decisions and the accuracy of predictive models.
- Forecasting models/time series analysis to examine portfolio trends and provide strategic tools for business projections.
- Model and campaign tracking to ensure effective model life cycle management and recommendations for redevelopment.
- Brainstorm new ideas and concepts
- Work with teammates on design and code reviews
- 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 standards.

**Requirements**:

- A degree in a numerate discipline, preferably Statistics / Mathematics / Operations Research (Honours / Master’s degree preferable)
- At least 3 years experience in predictive modelling or scorecard development and in 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 MYSQL, SAS, - SAS Enterprise Miner, R, Python, SPSS, MATLAB and BI tools such as QlikView, Power BI, and Tableau is required for technical domains, while experience in MDM, metadata, and data quality toolsets or platforms would be advantageous.
- Strong Data wrangling experience
- Knowledge of the credit industry and credit life cycle management
- Hands-on experience in 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 develop corporate performance management assets like KPIs, scorecards and dashboards.
- Be creative, flexible, think like an owner, maintain a high standard of work
- Have an understanding of Hadoop, Hive and/or MapReduce
- Experience with distributed computing is advantageous: Spark
- Experience with Cloud services is advantageous: AWS, Google
- Experience in working in an Agile/Scrum development environment
- Knowledge of the Retail tech industry is advantageous