Recently graduated with a B.Sc. in Computer Science and Engineering from Dhaka International University (CGPA 3.81 out of 4.00). Over the past several months, I've built four independent, end-to-end data analytics projects—covering inventory optimization, logistics performance, sales analytics, and supply chain cost analysis—using SQL Server, Power BI, Excel, and Python to turn raw business data into clear, actionable insights for stakeholders.
I'm currently looking to start my career as a data analyst, reporting analyst, or MIS executive in Dhaka, where I can apply my analytical and technical skills to solve real business problems while continuing to grow, learn, and take on more responsibility over time.
2022 – 2026
BSc · Computer Science and Engineering · 3.81
CSE graduate
An end-to-end data analytics project that identifies dead stock, segments inventory by revenue and demand volatility, and builds a proactive reorder system for a simulated FMCG retail company in Bangl
💬 "Our warehouses are full, but we're out of cash. And customers still complain we're out of stock."
RetailMart BD—a mid-sized FMCG retailer operating 3 warehouses and managing 35 SKUs—had no data-backed system to answer three basic questions:
📦 Which products have been sitting in the warehouse for months, silently blocking working capital?
⚠️ Which products are in high demand but at risk of stocking out?
🔄 When is the right time to reorder, and how much should be ordered?
Without answers, the company was caught between two contradictory problems at the same time—overstocking and stockouts—pointing to inefficiencies across procurement, warehousing, and sales simultaneously.
End-to-end logistics & delivery performance analysis for a fictional Bangladeshi distribution company — built entirely in Microsoft Excel (Power Pivot, DAX, PivotTables, Dashboard).
Shohoz Express Ltd. is experiencing a sustained decline in delivery performance, with an overall On-Time Delivery (OTD) rate of just 54.52%—far below the industry benchmark of 85%+. This project analyzes 12 months of shipment data to identify the root causes of delay across carriers, regions, routes, and operational timing. The analysis reveals that the problem is structural rather than seasonal, driven by specific underperforming carriers and route-level inefficiencies. Three targeted, actionable recommendations are provided to guide management's immediate intervention.
End-to-end sales pipeline using Medallion Architecture. Transformed messy CRM & ERP data into actionable business insights using SQL Server and Excel.
This project builds a complete SQL Server data warehouse using the Medallion Architecture, transforming 6 fragmented CRM/ERP source files (75,000+ raw records) into a clean, analytics-ready Star Schema. Using that warehouse, I analyzed $29.35M in revenue across 18,484 customers to uncover concrete business insights — from a near-total revenue dependency on two bike product lines, to a bimodal dead-stock pattern signaling planned product discontinuation — each backed by a specific, actionable recommendation.
End-to-end supply chain cost leakage analysis for a fictional Bangladeshi FMCG company — identifying ৳29.22 lakh in hidden costs across Procurement, Inventory, Logistics, and Fulfillment, with a prior
Bongo Consumer Products Ltd. (BCPL) is a fictional Bangladeshi FMCG company whose supply chain costs grew 18% over 2025 while revenue grew only 7%. Management had no visibility into where the money was going—or how to stop it.
This project builds a complete cost leakage diagnostic and recovery framework from the ground up: a Python data pipeline generating and cleaning synthetic supply chain data, a SQL Server star schema with 7 analytical views calculating leakage by supplier, route, and warehouse, and a 6-page Power BI dashboard delivering executive-ready insights with a prioritized 7-point recovery action plan.