Responsibilities
Strategy Input and Implementation

• Contribute to the strategic vision for AI/ML and data engineering, ensuring alignment with business goals.
• Identify opportunities where AI/ML can create competitive advantages, enhance customer experience, and drive revenue growth.
• Guide the adoption of emerging AI trends, including generative AI and LLMs, to maintain technological leadership.
• Partner with business leaders to define key AI/ML initiatives that align with corporate objectives.
• Stay ahead of industry trends, ensuring the company remains a leader in AI/ML applications.
• Research and prototype new AI techniques, particularly in Generative AI and Large Language Models (LLMs).

 AI/ML Model Development & Optimization

• Design, develop, and implement AI/ML models to support predictive and prescriptive analytics.
• Continuously refine AI methodologies to improve efficiency and accuracy.
• Optimize AI algorithms for performance, scalability, and real-world applicability.
• Ensure AI models are explainable, bias-free, and aligned with ethical AI principles.
• Deploy models in production environments across cloud platforms (GCP, AWS, Azure, Oracle Cloud).

Data Engineering & Infrastructure Management

• Oversee data pipelines, ensuring efficient data collection, cleaning, and transformation.
• Develop scalable data architectures to support AI/ML workloads.
• Implement automation tools to streamline data processing and model training workflows.

Forecasting & Business Intelligence

• Develop forecasting models that improve decision-making and business planning.
• Leverage AI for real-time analytics and business insights.
• Implement AI-driven solutions for customer behavior prediction, market trends, and operational efficiency.
• Use AI to analyze competitor data, identifying industry trends and market gaps.
• Provide insights that inform product development, pricing, and go-to-market strategies.
• Benchmark AI/ML capabilities against industry leaders to maintain competitive positioning.

Budget, Cost Control & Reporting

• Optimize operational expenses while maximizing revenue generation.
• Provide regular financial reporting and forecasting on platform performance.
• Manage, monitor and control the budgetary needs for Programmes/ Projects in line with business objectives.
• Manage and optimise the budget, ensuring all expenditure is in line with the agreed budgets.
• Monitor costs and determine initiatives to increase efficiencies and optimise resources – maximise cost/benefit ratios .
• Where relevant, ensure Vendor and IT costs are effectively managed.

Data Visualisation and Storytelling

• Develop dashboards and reports using Tableau, PowerBI, and Databricks to communicate AI-driven insights.
• Present complex data in a clear and actionable manner to both technical and non-technical stakeholders.
• Drive a data-driven culture within the organization by enabling access to AI-powered insights.

Collaboration & Stakeholder Engagement

• Work closely with product, technology, and business teams to integrate AI solutions into company offerings.
• Translate business problems into AI/ML-driven solutions, ensuring commercial viability.
• Act as an AI/ML SME, providing guidance on best practices and ethical AI deployment.

Qualifications: 

• Minimum of 4-year tertiary degree in related field (Data Science, Mathematics, Statistics, Computer Science)
• Master’s degree is advantageous

Experience: 

• Minimum 5-6 years experience in data science with a bias to software engineering AI/ML
• Demonstrated experience in deploying AI solutions in cloud environments and integrating AI insights into business strategy.
• Experience working in a medium to large organisation
• Worked across diverse cultures and geographies advantages