Ramya Krishna Kolakalapudi

I fuse data engineering with storytelling to give both IT and Marketing a single source of truth. By rebuilding ServiceNow dashboards in Power BI and automating the data flow with Python and AWS, I put live ticket trends, campaign performance, and cost insights on one screen, reducing the ticket backlog by 1,200+ and speeding resolution time by 58%. This lets support teams respond faster, marketers spot weak campaigns early, and leaders make budget calls with confidence, no more manual updates, just real-time answers.

I brought data, design, and revenue goals together. With SQL, Python, and Power BI, I created a Digital Engagement Score that ranks leads across email, social, web, and app, guiding the team to high-value prospects and lifting conversions by 19%. I trimmed page-load times by tuning SEO and UX, then ran A/B tests on 90+ campaigns to surface what really drives sales. Channel-level P&L dashboards now show leaders where to shift spend and pricing for maximum margin, adding $310 K in recurring revenue, all from one clear, real-time view.

For a Fortune 20 bank, processed 10M+ records with Python to build and deploy a churn-prediction model. A Streamlit app let managers explore the results in real time, and the logistic regression (89% accuracy) flagged 12% of customers at risk, guiding targeted retention offers.

I rebuilt our client's SQL workflows to shape over 2M transaction records for clustering and market-basket analysis. The models uncovered clear cross-sell pairs and loyalty segments, letting the team predict future buying habits and adjust product bundles and campaigns in real time. In short, I turned raw sales data into simple insights the marketers could act on right away.

As Senior Analyst at Professionals Desk, I ran a five-member team that built a Snowflake data hub and automated it with Selenium, Power Automate, and SAP ERP feeds, slashing report turnaround 47% and cutting errors 26%. I streamed clean finance, sales, and marketing data into Power BI, Looker, and Tableau so leaders could track EBITDA, CAC, store P&Ls, and campaign ROI in real time. Using SQL, Python, and R, I delivered demand forecasts, A/B-test readouts, and customer-segment models that lifted retention 17%, trimmed excess stock, and generated $4.2 M in new revenue, all while ROI and variance dashboards guided budget, pricing, and capital decisions across 25+ business units.

Blended campaign analytics with financial oversight to show exactly how growth spending hit the bottom line. I integrated Salesforce and ad-platform data into SQL dashboards that tracked CAC, CTR, CPC, CVR, and CPL, then used multi-touch attribution plus A/B tests to shift budget to the highest-yield channels, lifting ROAS by 18%. In parallel, I ran quarterly P&L reviews and automated cost-tracking checks with Excel, uncovering expense leaks that trimmed operating costs by 16%. The result: a single, audit-ready view that tied marketing performance to financial health so leaders could invest with confidence.