Lochanreddy MallakuntaAnalytics portfolio

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Showing 5 projects.

Placeholder for DigiPae funnel analytics evidence
FeaturedFintech

DigiPae Payment and Product Analytics

Problem: Where do users and merchants encounter friction across signup, identity verification, bank linking, payment initiation, and successful completion—and which issues should be prioritized?

Outcome: A measurement framework for identifying friction across onboarding, verification, bank linking, and payment completion.

Tools: SQL · Excel · Power BI · Python

Placeholder for smart-city traffic and air-quality evidence
FeaturedSmart City

Smart-City Research Analytics

Problem: Where is traffic and PM2.5 pressure concentrated across monitored junctions, how do conditions change over time, and which early-warning signals should operators review first?

Outcome: Led data systems and BI reporting for an urban analytics prototype monitoring real-time traffic and PM2.5 across 5+ city junctions.

Tools: Python · SQL · Excel · Power BI

Placeholder for tax filing analytics evidence
FeaturedTax / Finance

H&R Block Tax Analytics & Automation

Problem: Where do filing workflows bottleneck, which error patterns need attention, and how can ETL and reporting automation improve processing efficiency and leadership visibility?

Outcome: Analyzed filing patterns and bottlenecks, restructured ETL pipelines for about 40% faster processing, and delivered Power BI dashboards with automated validation.

Tools: Excel · Power BI · SQL · Power Query · Python · DAX

Placeholder for healthcare anomaly detection evidence
FeaturedHealthcare

AI-Driven Healthcare Analysis & Reporting

Problem: Which health-metric patterns should receive additional review, how can anomaly detection reduce time-to-insight, and what access controls are required for trustworthy monitoring?

Outcome: Built an AI-powered anomaly detection and reporting workflow for critical health-metric patterns, paired with role-based BI dashboards for faster monitoring.

Tools: Python · SQL · Excel · Machine Learning

Placeholder for marketing attribution evidence
IndependentMarketing

Marketing Attribution and Customer Segmentation

Problem: Which channels and customer segments create valuable, retained customers rather than inexpensive but low-quality conversions?

Outcome: An analysis framework that distinguishes channel quality and retained customer value from low-quality inexpensive conversions using synthetic campaign data.

Tools: SQL · Python · Excel · Power BI