Manager, Data Science (Machine Learning)

Company Description

Standard Bank Group is a prominent financial services group focused on Africa, and an innovative player on a global level, offering a variety of opportunities for career enhancement. We work alongside some of the most talented and driven professionals in the sector. Our range of clients include individuals, businesses of all sizes, affluent families, and large multinational corporations and institutions. We are enthusiastic about stimulating growth in Africa. We aim to bring true and meaningful value to our clients and the communities we serve, offering a tangible sense of purpose for our teams.

Job Description

The role involves assisting with advanced analytics and providing deep insights. This is achieved through proactive involvement in delivering customer-centered data analytics. The job includes using alternative methods for aggregating raw data (both internal and external). These methods will influence how we understand and react to customer behaviors and health, i.e., identifying risks and opportunities. The role will also entail implementing machine learning to challenge and improve predictive modeling techniques, available characteristic universe across the customer life cycle, and optimizing segmentation to enhance model performance. Solutions should satisfy customer centricity and digitization objectives. The role includes tasks such as extracting meaningful insights from data, predictive modeling and machine learning, stakeholder engagement, leadership, and people management.

Qualifications

Minimum Qualifications:

• Type of Qualification: Post Graduate Degree
• Field of Study: Mathematical Sciences
• Other minimum qualifications or professional memberships: An Honours degree, with majors in Statistics, Applied Mathematics, Econometrics, Actuarial Sciences, or Engineering.

Experience Required:

• 5-7 years experience in advanced analytics, combined with adequate knowledge of products and customer behavior in a financial services environment.
• Experience managing a quantitative team at a junior management level and experience with data mining and retail credit risk modeling.
• Communication skills required, particularly the ability to explain technical concepts to a non-technical audience.
• Team management and leadership experience, along with interaction at an executive level. Coding ability is necessary, and candidates should have experience dealing with large datasets (preferably in SAS, R, Python, or SQL).
• Some experience in machine learning modeling techniques, along with an understanding of underlying details and parameters. Candidates should have good analytical problem-solving skills.
• Experience in developing machine learning or AI models.
• Experience working with container technologies such as Docker, Kubernetes.
• Experience with cloud-based infrastructures like Azure and/or AWS with their associated MLOps tools.

Additional Information

Behavioral Competencies:

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

Technical Competencies:

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