MIS Analyst

Role Overview

The MIS Analyst will serve as the organization’s data backbone—responsible for collecting, analyzing, and reporting business-critical information across verticals. The candidate will be expected to design and maintain dashboards, streamline reporting systems, and deliver actionable insights that drive strategic and operational decision-making.

Key Responsibilities

• Develop, automate, and manage MIS reports and dashboards for management review (daily/weekly/monthly).
• Extract, clean, and analyze data from multiple internal and external systems (ERP, CRM, accounting tools, etc.).
• Conduct variance analysis of sales, expenses, and profitability to identify trends and anomalies.
• Partner with business units to understand key metrics and convert data into business intelligence.
• Maintain database accuracy and integrity by ensuring consistent data flow and validation processes.
• Prepare KPI scorecards and visual dashboards (Power BI / Tableau / Excel) for leadership presentations.
• Build forecasting, budgeting, and financial modeling reports to support strategy and operations.
• Coordinate with IT and Finance teams for data migration, system integrations, and process automation.
• Support ad-hoc analysis requests from management with data-backed recommendations.

Qualifications

• Bachelor’s degree in Business Administration, Finance, Economics, Statistics, or Computer Science.
• 2–5 years of experience in MIS, Business Analytics, or Financial Reporting.
• Strong proficiency in Advanced Excel, Power Query, and VBA (mandatory).
• Working knowledge of Power BI / Tableau / SQL preferred.
• Understanding of business processes, financial statements, and KPIs.
• Excellent attention to detail and high data accuracy.
• Strong communication and presentation skills with the ability to explain insights to non-technical stakeholders.

Key Competencies

• Data interpretation & visualization
• Analytical problem-solving
• Business acumen & cross-functional coordination
• Process automation mindset
• Confidentiality and data governance awareness
• Performance MetricsTimeliness & accuracy of reports
• Insight quality (impact on management decisions)
• Data reliability improvement
• Reduction in manual reporting time
• Adoption rate of dashboards and automated tools