Skip to content
View DataWithSoumya's full-sized avatar
🎯
Focusing
🎯
Focusing

Block or report DataWithSoumya

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
DataWithSoumya/README.md

Hi, I'm Soumya 👋

Senior Data Analyst with 5+ years in Retail & CPG Analytics. I turn messy transactional data into decisions — using SQL, Python, and Power BI.

At work, I build BI dashboards and KTLO reporting pipelines for retail clients. Here, I use the same tools to dig into questions I find interesting — pricing, churn, segmentation, supply chain — end-to-end, from raw data to a business recommendation.

🔭 Currently deepening SQL query optimization and data modeling through a self-directed 100 Days of SQL challenge.

📌 Featured Projects

A/B Testing: Checkout Redesign Two-proportion z-test and sample ratio mismatch checks to evaluate a checkout redesign — with segment-level significance testing to catch effects hidden in the topline number.

Customer Segmentation (RFM + K-Means) Unsupervised segmentation to find where revenue actually concentrates — turned into segments a marketing team can act on, not just clusters on a chart.

Retail Supply Chain Analytics End-to-end SQL + Python + Power BI project: stockout root-cause analysis, supplier scorecarding, and demand forecasting for a retail chain.

Pricing Strategy Analysis Price elasticity by category, competitor benchmarking, and discount ROI — built to answer "where are we leaving money on the table?"

Churn Analysis Root-cause analysis of customer churn, a prediction model, and a churn playbook the business could actually use.

Marketing ROI Analysis Campaign ROI and CAC across channels, using Python and SQL to cut through vanity metrics.

🛠️ Tools I work with

SQL Python (pandas, NumPy) Power BI (DAX, data modeling) Advanced Excel (VBA, Pivot Tables) Jupyter Notebook

📫 Reach me

LinkedIn · soumyaranjanmishra2411@gmail.com

Pinned Loading

  1. ab-testing-checkout-analysis ab-testing-checkout-analysis Public

    Statistical A/B test analysis of a checkout redesign — two-proportion z-test, sample ratio mismatch check, and segment-level significance testing using Python and SQL.

    Python

  2. customer-segmentation-rfm customer-segmentation-rfm Public

    Unsupervised customer segmentation using RFM analysis and K-Means clustering — identifies actionable customer segments and revenue concentration using Python and SQL.

    Python

  3. retail-supply-chain-analytics retail-supply-chain-analytics Public

    End-to-end SQL + Python + Power BI supply chain analytics — stockout root cause analysis, supplier scorecarding, and demand forecasting for a retail chain.

    Python

  4. pricing-strategy-analysis pricing-strategy-analysis Public

    Data-driven pricing strategy analysis — price elasticity by category, competitor benchmarking, discount ROI, and bundling recommendations using Python & SQL.

    Python

  5. churn-analysis churn-analysis Public

    Root cause analysis of customer churn using Python and SQL — segment analysis, churn prediction model, and an actionable churn playbook

    Python

  6. marketing-roi-analysis marketing-roi-analysis Public

    Python + SQL analysis of marketing campaign ROI and CAC across channels

    Python