Data Analyst

Key Responsibilities

A. Data Collection & Integration

• Gather, clean, and process data from multiple systems including SAP, CRM, ERP, and IoT-based plant systems.
• Collaborate with IT and business teams to ensure data accuracy, consistency, and completeness.
• Integrate data from diverse functions Sales, Production, Finance, HR, and Logistics — into centralized analytics platforms.
• Establish automated pipelines to minimize manual data handling.

B. Business Intelligence & Reporting

• Develop interactive dashboards and analytical reports using Power BI, Tableau, or SAP Analytics Cloud.
• Track key metrics such as production efficiency, dispatch performance, sales realization, logistics cost, and working capital.
• Build automated KPI reports for leadership, highlighting trends, variances, and improvement opportunities.
• Maintain real-time visibility into business performance through digital dashboards.

C. Analytical Modeling & Forecasting

• Perform trend, variance, and root cause analyses to support production planning and demand forecasting.
• Create predictive and prescriptive models to improve sales forecasting, cost optimization, and logistics efficiency.
• Support data-backed decision-making for price strategies, customer targeting, and budget control.
• Evaluate performance improvements from implemented analytics solutions.

D. Process Automation & Data Governance

• Identify opportunities to automate recurring reports and reduce manual interventions by 20–30%.
• Implement data validation and audit checks to ensure data accuracy and governance.
• Document standard data models and reporting templates for organization-wide use.
• Ensure compliance with ACL’s data privacy and IT governance frameworks.

E. Collaboration & Stakeholder Engagement

• Partner with Sales, Operations, Finance, and HR teams to translate analytical insights into business action plans.
• Present analytical findings to senior management through structured dashboards and visual storytelling.
• Support functional heads with ad hoc analysis and customized reports.
• Collaborate with digital transformation teams to enhance BI adoption across functions.

F. Continuous Improvement & Innovation

• Drive data literacy initiatives to upskill users across functions.
• Introduce AI/ML-based analytics for operational forecasting and optimization.
• Benchmark ACL’s analytics practices with industry peers to drive continuous improvement.
• Contribute to the development of a data-driven culture across the organization.