Purpose Statement

• 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 Capitecs 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.

Candidate Requirements

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.

Knowledge:

• 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

Functional Skills:

• 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.)