Madhukar Katikala

About Madhukar Katikala

Dedicated 3+ years of professional experience as a Data Analyst proficient in Python (Pandas, NumPy, SciPy), SQL, Tableau, Apache Kafka, NLP, FHIR, HL7, Apache Spark, Airflow, Power BI, AWS SageMaker. Expertise in data analysis, visualization, real-time data streaming, machine learning pipeline development, ETL design, statistical analysis and regulatory compliance. Experience building dashboards, implementing data lake architectures (Azure), integrating APIs and automating reporting systems. Skilled in data masking, encryption and fraud detection.

Experience

1. Data Analyst

   Kaiser Permanente

   May 2024 — Present · CA, US

   Performed advanced data analysis on large-scale patient datasets using Python (Pandas, NumPy, SciPy) and SQL, identifying key trends in hospital efficiency, patient outcomes and readmission rates, leading to a 15% reduction in patient readmissions.• Developed and deployed interactive Tableau dashboards for real-time patient monitoring and resource utilization tracking, enabling faster clinical decision-making and reducing response time by 30%.• Implemented real-time data streaming solutions using Apache Kafka, ensuring seamless ingestion of patient vitals into a centralized database, reducing data latency by 40%.• Leveraged Natural Language Processing (NLP) models to analyze unstructured physician notes and automate disease trend detection, improving early diagnosis accuracy by 20%.• Ensured HIPAA and PHI compliance across all data processing pipelines, implementing data masking and encryption strategies, reducing security incidents by 25%.• Integrated Fast Healthcare Interoperability Resources (FHIR) and HL7 data exchange standards, enhancing cross-system data interoperability by 35% and streamlining electronic health records (EHR) integration.• Designed and optimized ETL pipelines using Apache Spark and Airflow, increasing data processing efficiency by 35% and reducing batch processing time from hours to minutes.• Conducted statistical analyses (A/B testing, hypothesis testing and regression modeling) to assess treatment effectiveness, patient recovery rates and operational performance, improving data-driven decision making.• Performed root cause analysis on medication error patterns using Python and SQL, leading to a 20% decrease in prescription errors and adverse drug events (ADEs).• Led the implementation of Azure-based data lake architectures, improving data accessibility and integration across multiple healthcare departments, reducing data silos and enhancing collaboration.

Education

• California Baptist University

  Master's degree

  2023 — 2024