An AI Specialist within the Business Analysis COE plays a pivotal role in integrating artificial intelligence solutions to enhance the capabilities and eciency of business analysts. This position aims to leverage AI technologies to automate routine tasks, provide data-driven insights, and support decision-making processes. By implementing AI initiatives, the AI Specialist ensures that business analysts are equipped with advanced tools and methodologies, enabling them to focus on more strategic and analytical aspects of their role. Furthermore, the AI Specialist collaborates with cross-functional teams to identify areas where AI can drive significant improvements, thereby contributing to the overall mission of promoting best practices and continuous improvement within the bank.

Essential Qualifications - NQF Level

• A bachelor's degree in computer science, Data Science, Artificial Intelligence, or a related field.

Preferred Qualification

• Proficiency in programming languages such as Python, Jave, C++, or R, and experience with AI and machine learning frameworks.

Minimum Experience Level

• 3+ years solid AI experience

Types of exposures

• Proven working knowledge of Confluence and Jira for Cloud.

• Proven working knowledge of ARIS.

• Familiarity with machine learning algorithms, AI frameworks, and data visualization tools.

• Experience with data analysis tools and techniques.

• Natural Language Processing (NLP) including techniques for text classification, sentiment analysis, and language modelling and familiarity with NLP libraries.

• Knowledge of cloud computing and cloud platforms like AWS, Google Cloud, and Azure for deploying AI models.

• Advanced knowledge of Jira and Confluence in the Cloud.

• Proven experience in AI, machine learning, and data science.

• Excellent understanding of data structures, data modelling, and software architecture.

Key responsibilities of the AI Specialist in the BA COE include:

AI Integration:

Identifying and integrating AI solutions that can augment the capabilities of business analysts, thereby improving their eciency and eectiveness.

Automation:

Developing and implementing AI-driven automation for routine tasks to free up business analysts to concentrate on strategic and analytical functions.

Data Analytics & Insights:

Utilizing AI to derive actionable insights from data, facilitating informed decision-making processes within the bank.

Collaboration:

Working closely with cross-functional teams to pinpoint and prioritize areas where AI can bring about significant performance enhancements.

Best Practices:

Promoting and embedding AI best practices across the business analysis community to ensure consistency and high standards.Training & Development:

Providing training and resources to business analysts on AI tools and methodologies to ensure they are well-equipped to leverage these technologies.

Continuous Improvement:

Monitoring and assessing the impact of AI initiatives on business analysis performance and iterating to drive continuous improvement.