Decision Scientist (Sandton)
Sandton, GT, ZA
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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
- 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.
Education (Minimum)
- Honours Degree in Mathematics or Statistics
- Grade 12 National Certificate / Vocational
Education (Ideal or Preferred)
- Masters Degree in Mathematics or Statistics
Experience and Knowledge
Minimum Experience and Knowledge:
- Length of experience required is also conditional on qualifications obtained
- Statistical (predictive and classification) model development and deployment principles and techniques; including 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.)
- At least one Machine Learning language (e.g., Python or SAS Viya)
- Business analysis and requirements gathering
- General business know-how (e.g., risk, compliance, operations - such as NCR, POPIA, and SARB)
- Cloud environments (e.g., Azure, AWS, and large relational databases)
- Functional business area (e.g., Credit) environment knowledge and experience
- Developing scorecards from scratch
- Underlying theory and application of machine learning models
- Best practices for decision science (such as reusability, reproducibility, continuous monitoring, etc.)
Ideal Experience and Knowledge:
- Over 5 years’ experience in an analytical science role
- Working with multiple teams to deliver predictive models into a production environment
- Financial sector
- Retail credit environment / industry (Credit cycle)
- Bank decision science lifecycle
Skills
- Numerical Reasoning skills
- Researching skills
- Planning, organising and coordination skills
- Attention to Detail
- Problem solving skills
- Decision making skills
- Analytical Skills
- Presentation Skills
- Communications Skills
- Interpersonal & Relationship management 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.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: AI strategy AWS Azure Banking Classification Data analysis Machine Learning Mathematics ML models Python RDBMS SAS Statistics
Perks/benefits: Career development
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