Turning raw operations data into decisions that hold up.

Md Ainain Ahmed — Data Analyst with hands-on experience in SQL, Python, Power BI and Tableau. I build the pipelines and dashboards that improve SLA compliance, cut manual reporting effort, and give stakeholders numbers they can act on.

View projects See experience

15 %

SLA compliance improvement across 500+ sellers in 6 months

40 %

Reduction in manual reporting effort via Excel dashboards

25 %

Improved data accuracy through validation & root-cause analysis

20 %

Faster issue resolution turnaround across cross-functional teams

01 About

I work at the intersection of operations and analytics — hands-on with SQL, Python, Power BI, Tableau and Excel, turning messy business data into dashboards and reports people actually use.

Most recently at Noon E-commerce , I analyzed merchant performance across 500+ sellers, built the Excel reporting layer operations teams relied on daily, and ran the data validation work that kept catalogue and onboarding data trustworthy.

Before that, I coordinated an education impact program in Bihar, tracking participation and learning outcomes for 200+ students — proof that the same rigor around KPIs and clean data applies well beyond e-commerce.

I'm currently building out independent analytics projects — from startup funding trends to customer RFM segmentation — to keep sharpening the pipeline-to-dashboard workflow end to end.

02 Skills

Analysis & visualization

SQL Python Pandas NumPy Matplotlib Seaborn Power BI Tableau Excel (Pivot, VLOOKUP)

Databases & tooling

MySQL ETL Pipelines Jupyter Git / GitHub Streamlit

Analytics & reporting

KPI Tracking Dashboard Development Data Cleaning & Validation Root-Cause Analysis RFM Segmentation Statistical Analysis A/B & Trend Analysis

Business

Stakeholder Reporting Cross-Functional Collaboration Process Optimization Requirement Gathering Business Intelligence

03 Experience

Nov 2024 — Dec 2025

Merchant Operations Agent

Noon E-commerce India Pvt. Ltd. · New Delhi

Analyzed merchant performance and operational KPI data across 500+ sellers , contributing to a 15% improvement in SLA compliance within 6 months.
Built and maintained Excel-based performance dashboards, cutting manual reporting effort by 40% and speeding up operations decision-making.
Ran data validation, cleansing and root-cause analysis on onboarding and catalogue data, improving accuracy by 25% .
Partnered with cross-functional teams to monitor fulfilment, cancellation and merchant health metrics, cutting issue resolution turnaround by 20% .

Aug 2024 — Oct 2024

Impact Assessment & Program Coordinator, Project 'ZAHEEN'

Bharats Youth Foundation (NGO) · Gayaji, Bihar

Managed and tracked participation and engagement metrics for 200+ underprivileged students across the Gaya division.
Analyzed attendance and learning-progress data in Excel, producing reports that lifted student participation by 20% .
Led computer literacy training and coordinated with volunteers, reducing administrative reporting effort by 30% .

04 Projects

Indian Startup Funding Analysis

ETL pipelines preprocessing 10,000+ funding records (2020–2025) into a modular BI dashboard with 20+ interactive views and 15+ KPIs — YoY/MoM growth, investor profiling, funding funnel and sector concentration.

Python Pandas NumPy Matplotlib Streamlit

GitHub Repository Live Dashboard

Customer Shopping Behavior Analysis

End-to-end pipeline from raw transactions to a MySQL analytics dataset. Window-function SQL for RFM segmentation found Clothing & Accessories drove ~60% of purchase volume; Power BI + DAX dashboard for AOV and subscription penetration.

Python MySQL Power BI DAX

GitHub Repository

Healthcare Data Cleaning & Quality Pipeline

End-to-end wrangling workflow across 4 linked clinical datasets (patients, treatments, adverse reactions), resolving missing values, invalid entries, and duplicates via regex-based validation and multi-table merges into analysis-ready data.

Python Pandas NumPy Jupyter Notebook

GitHub Repository

IMDb Top 250 Movies Web Scraper

Automated scraping pipeline with Selenium and BeautifulSoup to extract rank, title, year, duration, rating and review count from IMDb's dynamically loaded Top 250, cleaned and published as a reusable dataset.

Python Selenium BeautifulSoup Pandas

GitHub Repository Kaggle Dataset

05 Education