Nitish Kumar Manthri

Architected production-ready Streamlit dashboards for healthcare KPI monitoring, improving executive decision-making efficiency by 35% by automating reporting pipelines and replacing manual Excel workflows.

Designed and deployed scalable Python analytics applications using Flask/FastAPI on AWS (S3, Redshift, EMR), processing fragmented healthcare data with Docker containerization and GitHub Actions CI/CD pipelines.

Implemented ML-powered anomaly detection workflows and real-time alerting systems, reducing data processing time by 58% (from 12 to under 5 hours) while maintaining 99.5% system uptime.

Crafted interactive Power BI and Plotly visualizations with automated monitoring for data quality and latency, improving care satisfaction insights by 18% and supporting daily operational reviews.

Orchestrated complex ETL workflows using Airflow and dbt models, eliminating deployment bottlenecks and reducing release cycles from weeks to days.

Shipped production fraud detection Streamlit applications utilizing Isolation Forest models on Databricks, achieving 97% precision and preventing multi-million-dollar losses through real-time dashboard monitoring.

Engineered automated analytics pipelines with Kafka streaming and Spark, enabling instant anomaly alerts for high-risk financial activities and supporting rapid rate reviews for revenue managers.

Developed ARIMA forecasting models and A/B testing frameworks in Python, optimizing marketing spend decisions and improving campaign ROI by 25%.

Constructed performant SQL queries and window functions on Snowflake/MongoDB, consolidating siloed ETL processes and reducing system latency by 40% for near real-time business intelligence.

Established CI/CD best practices using Docker and automated testing, ensuring high code quality and documentation standards across the analytics stack.