Decision Scientist I

Purpose Statement

• To solve business problems, create new products and services and improve processes through using the disciplines of data science, quantitative (financial) analysis, and traditional scoring techniques, translating active business data into usable strategic information.
• To look at ways of analysing 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 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.

Education (Minimum)

Education (Ideal or Preferred)

Knowledge and Experience

Minimum Experience and Knowledge:
Experience:

• NB. Length of experience required is conditional on the qualifications obtained 
• Experience in statistical (predictive and classification) model development and deployment incl. traditional scoring (logistic regression with binning and missing value replacement e.g. reject inference), machine learning (neural networks, SVM, random forests etc.), and quantitative analysis (time value of money etc.)
• Basic business analysis and requirements gathering
• Working in cloud environments e.g. Azure, AWS and large relational databases 
• Experience in at least one ML language (e.g. Python or SAS Viya) 

Knowledge:

• Basic general business know-how: e.g. risk, compliance, operations e.g. NCR, POPIA, SARB
• Basic functional business area (e.g. Credit) environment knowledge and experience
• Understanding of statistical (predictive and classification) model development and deployment principles and techniques incl. traditional scoring (logistic regression with binning and missing value replacement e.g. reject inference), machine learning (neural networks, SVM, random forests etc.), and quantitative analysis (time value of money etc.).
• Relational database technologies

Ideal Experience:

• Financial sector experience

Skills

Additional Information