About the Role
Drive AI-driven automation and intelligent reporting across Finance and Operations to streamline and automate reporting processes.
This role focuses on reducing manual work, improving reporting speed, and enhancing data accuracy, enabling the business to make faster and better decisions.
This role requires a high level of integrity, as it involves handling sensitive financial data and supporting business-critical decision-making processes.
Key Responsibilities:
1) Reporting & Process Automation (Priority Focus)
- Automate weekly and monthly finance reports
- Eliminate manual Excel consolidation and repetitive tasks
- Develop standardized and scalable reporting templates
2) Data Management & Pipeline Development
- Extract and transform data from ERP and internal systems
- Ensure data accuracy, consistency, and integrity
- Build and maintain structured datasets for reporting and analytics
3) Dashboard & Visualization
- Develop interactive dashboards (e.g. Power BI / Tableau)
- Enable management to access near real-time insights
- Improve visibility of key KPIs (sales, cost, margin, etc.)
4) AI & Advanced Analytics (Progressive Implementation)
- Develop and deploy AI/ML models for:
- Forecasting (sales, cash flow, demand)
- Anomaly detection (cost, production, quality)
- Apply practical AI solutions to enhance automation and decision-making
5) Process Improvement
- Identify inefficiencies in current workflows
- Design automated solutions to improve productivity
- Reduce dependency on manual intervention and key personnel
- Ensure proper data governance, accuracy, and confidentiality in all reporting and automation processes.
6) Collaboration
- Work closely with Finance, Operations, and Production teams
- Translate business requirements into practical technical solutions
7) Other Duties
- Any other tasks as assigned by Top Management
Requirements
- Minimum Diploma or Bachelor’s degree in Computer Science, Engineering, Data Science, Artificial Intelligence or related field
- Proficiency in Python & SQL programming and foundational knowledge of AI and machine learning frameworks
- Understanding of AI modelling techniques, such as supervised and unsupervised learning, and familiarity with software development practices
- Strong problem-solving abilities with an aptitude for analysing datasets and troubleshooting technical issues
- Hands-on experience in model deployment & end-to-end pipeline
- Experience in at least ONE of forecasting/ time series/ computer vision for manufacturing industry or NLP/ automation.
- At Least 5 years’ experience in data engineering.
- Strong analytical mindset and ability to collaborate effectively in a team environment, with clear communication
- High level of integrity, with strong sense of responsibility in handling sensitive financial and operational data, ensuring accuracy, confidentiality, and ethical use of information.