Turning raw data into decisions. I build dashboards, models, and insights across retail, telecom, e-commerce, and content analytics — end to end.
I'm a CSE graduate and Data Analyst with a CGPA of 8.34 from Acharya Institute of Technology. My stack spans Python, SQL, Power BI, and Excel — but what I actually do is translate messy data into clarity that helps people make better calls.
I've built ML-powered apps, cohort dashboards, churn models, and customer segmentation systems — across 500K+ record datasets — deployed and presented to real stakeholders.
Trained a regression model on 300K+ synthetic cloud sales records using product, marketing, and cost signals. Deployed a 4-page interactive Streamlit app with live prediction, historical comparison charts, and feedback logging via CSV.
Built an interactive Power BI dashboard analyzing ₹2M+ in sales, 100+ orders, and 4 product categories. 6+ dynamic visualizations with slicers for city, month, and status. SQL + DAX to track top customers and monthly revenue across 4 cities.
Extracted and processed stats for 30+ videos via YouTube Data API v3, tracking 19K+ total views. Power BI dashboard identified 9–11 AM as peak upload window through temporal analysis; top video reached 1,600+ views with likes-vs-views KPI tracking.
Analyzed 6,400+ customer records across 32 attributes using MySQL and Power BI — identifying contract type, internet service, and tenure as key churn drivers. 3-page dashboard with 10+ DAX measures: 26.99% churn rate, $126K+ monthly revenue at risk, 2K+ high-risk customers.
Processed 500K+ UK retail transactions with Pandas. 3-page Power BI dashboard with retention heatmap, treemap, and KPI cards across 4,000+ products and 38 countries. Cohort analysis revealed sharp Month 1 drop-off; UK = 82% revenue, Q4 = peak period.
Clustered 8,950 credit card customers into 4 behavioral segments using K-Means with RobustScaler. Identified a 0.4% Credit Risk cluster with extreme minimum payment behavior — actionable signal for early collections. 3-page Power BI dashboard with segment-level spend and payment risk.
Open to Data Analyst roles, freelance dashboards, and interesting data problems. Drop a message or connect anywhere below.
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