Data Scientist

Company Description

Standard Bank Group is a leading Africa-focused financial services group, and an innovative player on the global stage, that offers a variety of career-enhancing opportunities – plus the chance to work alongside some of the sector’s most talented, motivated professionals. Our clients range from individuals, to businesses of all sizes, high net worth families and large multinational corporates and institutions. We’re passionate about creating growth in Africa. Bringing true, meaningful value to our clients and the communities we serve and creating a real sense of purpose for you.

Job Description

To assist with advanced analytics and deep insight by:

• providing customer centric data analytics, including alternative methods of aggregating raw data (internal and external), which will ultimately influence the way in which we view and act on customer behaviour and customer health, i.e. identifying risks and opportunities; and
• implementing the use of machine learning to challenge and improve predictive modelling techniques, the available characteristic universe across the customer life cycle and optimising segmentation to enhance model performance. Solutions should satisfy customer centricity and digitisation objectives.

Qualifications

Minimum Qualifications
Type of Qualification: Honours Degree
Field of Study: Mathematical Sciences
Other Minimum Qualifications, Certifications or Professional Memberships: Honours degree (with majors in Statistics / Applied Mathematics / Econometrics / Actuarial Sciences/Engineering)

Experience

Advanced Analytics

3-4 years experience in advanced analytics, combined with sufficient knowledge of products and customer behaviour in a financial services environment. Experience with data mining and retail credit risk modelling. Communication skills, in particular, communication of technical concepts to a non-technical audience. Coding ability and experience to deal with big datasets (preferably in SAS, R, Python or SQL). Some experience of machine learning modelling techniques, with an understanding of underlying details and parameters.  Good analytical problem-solving skills.

Additional Information

Behavioural Competencies:

• Generating Ideas
• Examining Information
• Exploring Possibilities
• Examining Information
• Developing Practical Approaches

Technical Competencies:

• Scientific Reasoning (ScR)
• Statistical Inference
• Data Analysis
• Data Integrity
• Strategic Planning and Reporting