Manager: Data Science Or Senior Data Scientist

Gauteng
- ,
- JHB - Northern Suburbs
- Plus Medical Aid, Pension Fund, Provident Fund, Preferential Banking Rates
- Our client, one of the biggest banks in South Africa based in Johannesburg who is a firm believer in technical innovation and leading-edge financial solutions is urgently looking for a Manager:
Data Science or Senior Data Scientist to assist with advanced analytics and deep insight by being a proactive partner in:
- providing customer centric data analytics, including alternative methods of aggregating raw data (internal and external), which will ultimately influence the way in which we view and act on customer behaviour and customer health, i.E. identifying risks and opportunities
- implementing the use of machine learning to challenge and improve predictive modelling techniques, the available characteristic universe across the customer life cycle and optimising segmentation to enhance model performance. Solutions should satisfy customer centricity and digitisation objectives
**In order to be considered the following is required**:
- Honours Degree in Mathematical Sciences
- Honours degree (with majors in Statistics / Applied Mathematics / Econometrics / Actuarial Sciences/Engineering)
- 5-7 years’ experience in advanced analytics, combined with sufficient knowledge of products and customer behaviour in a financial services environment
- Some experience in managing a quantitative team at a junior management level
- Experience with data mining and retail credit risk modelling
- Communication skills, in particular, communication of technical concepts to a non-technical audience
- Team management and leadership experience as well as interaction at executive level
- Coding ability and experience to deal with big datasets (preferably in SAS, R, Python or SQL)
- Some experience of machine learning modelling techniques, with an understanding of underlying details and parameters.
- Good analytical problem-solving skills
**Responsibilities**:
- Source data from various internal and external sources by building relationships with internal teams and external vendors
- Investigate the appropriate data storage and data mining tools to extract value from the sourced data
- Encourage data mining using state-of-the-art methods
- Draw inferences and conclusions, create dashboards and visualisations of processed data, trends, results
- Translate business problems into data questions in order to create innovative models and story tell the voice of our customers
- Build and test hypotheses, based on analytical findings to support proposed strategy changes or actions to be taken
- Share insights from all analyses performed
- Investigate the use of predictive analytics and machine learning techniques to solve complex problems and drive business decisions
- Ensure necessary peer reviews or validation of models is undertaken before deployment
- Build and maintain credible relationships with internal and external stakeholders
- Interaction with validation, where necessary, on model related queries
- Manage reporting and presentation of models to all forums
- Ensure that content is accurate and appropriate for the audience and that appropriate technical items are adequately contextualised and explained
- Mentor and motivate data scientists in the area to set the example on living the values and recognition.
- Contribute to the training plan to ensure appropriate upskilling of data scientists
- Coordinate the efforts of the data scientists under management to minimise duplication of effort, maximise efficiency and value for money
- Agree model development targets/goals and timelines with Head:
Data Science and monitor progress
- Take accountability for the overall achievement of project goals and timelines
- Responsible for performance reviews and setting of goals and development plans for direct reports
- Mentor team on data mining, machine learning and model development techniques and approaches
- Motivate team in the area to set the example on living the values and recognition
- Coordinate the efforts of the data scientists under management to minimise duplication of effort, maximise efficiency and value for money
Information displayed above not limited to advertisement. Please contact for further information.
- For more information please contact:
- Miller Mkandhla