Head Data Analytics & AI

To lead and build a strong data analytics and AI team that aims to drive the company towards becoming a data-first and data-driven organization by delivering and maintaining smart data-driven solutions crucial for growth and operations. The individual will accelerate the adoption and implementation of AI solutions to enhance efficiency, innovation, and competitive advantage. The position also involves managing all aspects of new data and AI projects from inception to delivery, as well as day-to-day operations, with a strong focus on assessing business value, ROI and reduce cost.

Key Responsibilities:

• Lead and build a strong data analytics and AI team over time and this should become possible organically by being able to demonstrate value
• Provide guidance and establish best practices and methodologies for data analytics and

  responsible

  AI initiatives.
• Manage and oversee stages of AI and LLM Projects, from initial assessment to implementation.
• Build and maintain close working relationships with the Business and Functions Process Owners to gather specific requirements and define the scope of work.
• Collaborate closely with internal staff, users, and third parties to ensure success.
• Develop and implement advanced models and algorithms to solve complex business problems.
• Respond to and resolve data mining performance issues. Monitor data mining system performance and implement efficiency improvements.
• Stay updated with the latest advancements in AI and LLM technologies and apply them to enhance project outcomes

Preferred Skills:

• Programming languages: Python, R or likes
• Understanding of algorithms like linear regression, logistic regression, decision and regression trees, random forest, boosting algorithms (e.g., XGBoost), k-means, hierarchical clustering, and principal component analysis
• Understanding of data science concepts: Statistics, probability, data transformation, visualization, storytelling, deep learning
• Statistical and Mathematical Methods: Application of statistics and prominent statistical models
• Good understanding of Data & AI technologies/tools: ML Ops, ETL, data lake, graph databases, NLK, Data Optimization