Capitec Bank
Decision Scientist (Sandton)
NewPayCompetitive
LocationSandton/Gauteng
Employment typeFull-Time
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Job Description
- Req#: 48526
- 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.
- To design quantitative advanced analytics models that answer business questions and/or discover opportunities for improvement, increased revenue, or reduced costs.
- Honours Degree in Mathematics or Statistics
- Grade 12 National Certificate / Vocational
- Masters Degree in Mathematics or Statistics
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We're on the lookout for energetic, self-motivated individuals who share our passion for service in the banking industry. To be part of the journey, follow the steps below:
1. To see what life at Capitec is all about and complete a short assessment, please click here!
2. Once you have completed the above finalize your application by clicking apply below
Purpose Statement
Education (Minimum)
Education (Ideal or Preferred)
Knowledge and Experience
Minimum Experience:
- NB. Length of relevant work experience required is also conditional on the qualifications obtained
- Deep understanding of and expert experience in state of the art 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.)
- General business know-how / acumen: (e.g., risk, compliance, operations; e.g., NCR, POPIA, SARB)
- Business analysis and requirements gathering
- Working in cloud environments (e.g., Azure, AWS, and large relational databases)
- Experience in at least two Machine Learning languages (e.g., Python or SAS Viya)
- Expert functional business area (e.g., Credit) environment knowledge and experience
Minimum Knowledge:
- Deep understanding of state of the art 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.) and can teach to a broad and wide technical audience
- Underlying theory and application of machine learning models; able to understand underlying principles and theory, and able to teach others
- Best practices for decision science (such as reusability, reproducibility, continuous monitoring, etc.)
- Technical understanding
- Developing scorecards from scratch
Ideal Knowledge and Experience:
- Over 6 years’ experience in an analytical science role
- Financial sector experience
- Retail credit environment / industry (credit cycle)
- Working with multiple teams to deliver predictive models into a production environment
- Stakeholder relationship engagement and management at Senior Management and Executive levels
- Capitec Decision Science lifecycle
- Project management methodologies
Skills
- Planning, organising and coordination skills
- Numerical Reasoning skills
- Attention to Detail
- Problem solving skills
- Decision making skills
- Analytical Skills
- Researching skills
- Presentation Skills
- Interpersonal & Relationship management Skills
- Communications Skills
Additional Information
- Clear criminal and credit record
Capitec is committed to diversity and, where feasible, all appointments will support the achievement of our employment equity goals.