Data Scientist II: Credit: Collections and Recoveries at Capitec Bank

Purpose Statement

• Picture yourself in the heart of a dynamic, fast-paced environment, where you can harness the power of data to make a real impact. As a member of the Credit Collections & Recoveries data and decision science team at Capitec Bank, you'll be at the forefront of driving strategic insights and leveraging data as a competitive advantage. Collaborating with a multi-disciplinary, agile team, you'll apply your algorithmic, data mining, predictive modelling, machine learning and statistical expertise to extract, analyze and interpret data from a variety of sources, unearthing hidden trends and patterns that will help guide the business towards success. Join us in shaping the future of finance and unlock your true potential at Capitec Bank.

Education (Minimum)

• Honours Degree

Education (Ideal or Preferred)

• Masters Degree

Knowledge and Experience

Minimum

Knowledge: 

• Solution and experimental design for model development
• 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 SourceTree
• Relational database technologies
• Data Science lifecycle and applicable skills within

Experience:

• 2-5 years working experience in data science, machine learning and integration of developed solutions 
• Business analysis and requirements gathering
• Reproducible coding experience and working with source control tools e.g. Git, Bitbucket
• Experience in deploying models into production
• Spark, Hadoop or similar big data coding experience 
• Working in remote environments, e.g. Docker, Linux
• Working in cloud environments, e.g. Azure, AWS

Ideal

Knowledge:

• Data analysis 
• Solution and experimental design
• Machine learning model architecture (technical design and implementation processes)
• Specialist in one or more specific machine learning competencies, e.g. NLP, Deep Learning etc.

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 data science 
• Ethical AI design principles
• Capitec Data Science lifecycle 
• Capitec DPLC

Experience:

• Exposure to leading in multiple functional/technical areas

Skills

• Analytical Skills
• Attention to Detail
• Communications Skills
• Numerical Reasoning skills
• Problem solving skills

Additional Information

• Clear criminal and credit record