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- To solve business problems, create new products and services and improve processes through using the disciplinces of data science, translating active business data into usable strategic information.
- To look at ways of analyzing and optimising data as it relates to a specific business area; framing data analysis in terms of the decision-making process for questions or business problems posed by a stakeholder.
- To help build and deliver Capitec's AI/Machine Learning strategy, enabling data-led and improved business decision making. Design quantitative advanced analytics models that answer business questions and/or discover opportunities for improvement, increased revenue or reduced costs.
Qualifications & Experience
- Degree in Mathematics | Statistics | Data Science | Business Analytics | Engineering | Computer Science Plus 4+yrs relevant work experience. OR
- Hons Degree in Mathematics | Statistics | Data Science | Business Analytics | Engineering | Computer Science Plus 3+yrs relevant work experience. OR
- Masters Degree in Data Science or relevant discipline e.g. Mathematics, Statistics, Engineering, Computer Science.
- Functional business area (e.g. Credit) environment knowledge and experience
- Regulatory requirements e.g. NCR, POPIA, SARB
- Business analysis, requirements gathering, translating into business requirement specifications and designing and delivering business solutions.
- With modern software development best practices.
- Working in cloud environments, e.g. Azure, AWS
- Different operating systems / databases / programming language
- Predictive modelling techniques (statistical and machine learning) and deployment
- Extracting, aggregating, cleaning and analysing data from large relational databases
- Data Science lifecycle and applicable skills within
- Programming; Data base manipulation | Data Exploration Visualisation
- Statistical model development
- Advanced Computer literacy and programming (Office Suite, Working on different OS environments, e.g. working on remote Linux environment and dockerising machine learning models)
- Building and deployment of models
- ML language, for example SQL SAS
- Version Control
- Ability to productionalise and solution design
- Ability to learn, understand and apply complex machine learning methodologies
- Functional domain skill of the (e.g. credit) environment
- Capability to identify and define and solve the business problem i.e. application of domain know how and problem solving.
- Cloud computing (navigating on cloud vs on prem.)
- Clear credit and criminal record
