Koushik Gandham

About Koushik Gandham

I am a results-driven Data Analyst with hands-on experience in the healthcare and financial sectors, specializing in transforming complex datasets into actionable insights that drive strategic decision-making. With a Master\'s in Data Science from Stevens Institute of Technology and a proven track record at firms like Wells Fargo and Deloitte, I bring a strong foundation in data analytics, machine learning, and cloud technologies. My core expertise lies in:*Healthcare & Financial Data Analysis using SQL, Hive, and Python *Interactive Dashboard Development with Tableau and Power BI for real-time KPIs *ETL and Data Pipeline Automation using Apache Airflow and Spark *Cloud Data Integration on AWS and GCP, ensuring secure, scalable analytics *Compliance with industry standards such as HIPAA, maintaining data integrity I have applied machine learning for patient segmentation, anomaly detection, and operational forecasting, enhancing outcomes across departments. My passion lies in solving real-world problems through data and enabling data-driven culture across organizations.

Experience

1. Data Analyst and Engineer

   Verizon

   Jan 2023 — Present

   Architected a distributed ETL framework leveraging Apache Spark, Python, and AWS Redshift to process andintegrate 2+ TB of daily network telemetry, billing, and customer interaction data, delivering a scalable,query-optimized data warehouse for enterprise analytics.• Designed and deployed 15+ advanced Tableau dashboards with dynamic parameters and drill-downs,enabling leadership to monitor KPIs such as churn risk, call center efficiency, and service quality, driving a14% reduction in attrition across multiple business units.• Engineered 300+ derived features from network logs, transaction histories, and usage patterns incollaboration with data scientists, significantly enhancing predictive modeling for fraud detection, customersegmentation, and retention strategies.• Automated 18+ ingestion and transformation pipelines using Apache Airflow with integrated error handling,SLA monitoring, and real-time alerting, reducing manual intervention by 80% and improving systemreliability.• Developed ARIMA and time-series forecasting models on multi-year network and usage datasets, achieving92% accuracy in predicting peak loads, enabling proactive bandwidth allocation and resource optimization.• Deployed machine learning models (random forest, gradient boosting) in production to identify high-valuechurn-risk customers and anticipate high-cost service events, increasing retention by 15% and reducingcustomer support escalations.• Implemented enterprise-grade data governance controls including column-level encryption, fine-grained IAMpolicies, and automated lineage tracking to safeguard 500GB+ of sensitive financial and customer data incompliance with regulatory standards.• Instituted a comprehensive data quality management framework validating 100+ mission-critical fieldsacross staging and production environments, elevating reporting accuracy to 99.7% and ensuring auditreadiness.

Education

• Stevens Institute of Technology

  Master's degree