Data Analyst

Role Purpose

To ensure data accuracy and provide timely, insightful reports that support sales growth and business decision-making. The Data Analyst will be responsible for preparing and validating daily, weekly, and monthly reports, coordinating with sales teams and management, and leveraging analytical tools, including Excel, Power BI, Python, and AI-powered tools, to analyze sales and inventory performance, identify trends, and generate actionable business insights.

Salary CTC:

Location:

Key Responsibilities

1. Prepare and share Daily Sales Reports (DSR) with management and sales teams.
2. Verify sales reports received from stores and sales managers to ensure data accuracy, completeness, and consistency.
3. Generate month-end reports on sales performance, stock on hand (SOH), and inventory movement.
4. Prepare and share sell-through data by brand, category, and period to support sales and inventory tracking.
5. Prepare brand-wise Tradeshow Booking Quantity reports and share them with management for review, analysis, and planning.
6. Create and deliver business-specific reports, dashboards, and performance summaries as per management requirements.
7. Coordinate regularly with sales managers, store managers, Head Office (HO) teams, and warehouse teams for data collection, verification, and validation.
8. Ensure accurate and timely tracking of sales inflow, outflow, and inventory movement data.
9. Maintain, analyze, and visualize data using MS Excel, Power BI, Python, and other relevant analytical tools.
10. Leverage AI-powered tools to analyze large datasets, identify sales trends and patterns, detect anomalies, highlight performance gaps, and generate actionable business insights.
11. Use AI-assisted analytics to support sales forecasting, inventory planning, sell-through analysis, brand performance evaluation, and data-driven decision-making.
12. Explore opportunities to automate repetitive reporting tasks and improve reporting efficiency using AI tools, Python, and Power BI.
13. Support the sales team with ad-hoc analysis to identify growth opportunities, underperforming brands or categories, and potential inventory risks.
14. Validate AI-generated outputs and insights against source data to ensure accuracy, reliability, and business relevance.
15. Ensure responsible use of AI tools by maintaining data confidentiality, following company policies, and protecting sensitive business information.
16. Maintain proper documentation, version control, and backups of reports for audit, reference, and future analysis.
17. Demonstrate teamwork, time management, problem-solving, and attention to detail in all deliverables.

Skills & Experience Required

1. Graduate in Commerce, Business, Statistics, Computer Science, or a related field.
2. 2–4 years of experience as a Data Analyst, MIS Executive, Reporting Analyst, or in a similar role.
3. Strong proficiency in MS Excel, Power BI, and Python for data analysis, reporting, visualization, and automation.
4. Knowledge of sales reporting, inventory management, stock on hand (SOH), sell-through analysis, and sales performance tracking.
5. Working knowledge of AI-powered data analysis tools and the ability to use AI to identify trends, patterns, anomalies, and actionable insights from business data.
6. Ability to use AI-assisted tools for report preparation, data interpretation, forecasting support, and improving analytical productivity.
7. Understanding of data validation, quality checks, and verification of AI-generated analysis before presenting findings to management.
8. Strong analytical and problem-solving skills, with the ability to translate data into meaningful business recommendations.
9. Excellent time management, accuracy, and attention to detail.
10. Good communication and coordination skills for working with sales managers, store teams, Head Office, and warehouse personnel.
11. Ability to manage multiple reporting requirements and deliver accurate reports within defined timelines.
12. Willingness to learn and adopt new AI tools, analytical techniques, and reporting technologies to improve business efficiency.