Our client in the Banking industry is looking for Data Scientist in the Decision Science area, with about 2 years of experience. The ideal candidate will work under close supervision to ensure best practices are followed.
The purpose of the role is delivering business solutions via a collaborative approach involving mathematical formulae, business tactics, technological applications, statistics, data science and behavioural sciences to help senior management make data driven decisions within the retail credit risk environment.
Data scientists will help automate and improve processes, create new products and services and assist with improved decision making based on data within the retail credit risk environment.
Proven experience in:
- 2+ years of experience in building credit risk models (standard models like logistic regression and/or machine learning models) in Python/R/SAS
- Business analysis and requirements gathering
- Extracting and aggregating data from large relational databases
- Data mining and predictive modelling
- Reproducible coding experience and working with source control tools e.g., Git, Bitbucket
- Working in cloud environments, e.g., Azure, AWS
- Honours Degree in Data Science or Mathematics (Minimum)
- Masters Degree in Data Science or Mathematics (Ideal or Preferred)
Must have detailed knowledge of:
- Analytics and data analysis
- Credit life cycle / Retail credit environment and industry
- Modelling and implementation lifecycle
- Solution and experimental design for model development
- Statistical modelling and machine learning development and underlying theory and assumptions of techniques.
- Predictive modelling techniques (statistical and machine learning) and deployment
- Source control systems e.g., Git, Bitbucket, or Source tree
- Relational database technologies
- Data Science lifecycle and applicable skills within
- Solution and experimental design
- Machine learning model architecture (technical design and implementation processes)
- Interpretation of user requirements and translation into business requirements specifications
Solid understanding of:
- Underlying theory and application of machine learning models must be able to understand underlying principles and theory and be able to teach others.
- Best practices for statistical credit risk modelling and data science
- Ethical AI design principles
- Data Science and Modelling lifecycle
- Numerical Reasoning skills
- Critical thinking
- Attention to Detail
- Communications Skills
- Computer Literacy (MS Word, MS Excel, MS Outlook)
- Problem solving skills
- Analytical Skills
- SAS / SQL / Python Skills
- Interpersonal & relationship management skills
- Delivering Results and Meeting Customer Expectations
- Applying Expertise and Technology
- Learning and Researching
- Writing and Reporting
- Presenting and Communicating Information
Conditions of Employment
- Clear criminal and credit record
- Only shortlisted candidates will be contacted. Should you not hear from us after 30 days you may consider your application unsuccessful
- In keeping with our clients employment equity requirements, only South African citizens will be considered.
- Please include your current salary and salary expectations.