Saisrikar Kandukuri

About Saisrikar Kandukuri

Data Analyst specializing in large-scale analytics, predictive modeling, and business intelligence. I focus on transforming complex datasets into actionable insights that drive cost savings, operational efficiency, and strategic decision-making.My experience includes building end-to-end analytics solutions across healthcare and customer analytics domains. I have processed datasets exceeding 500K healthcare claims and 2M+ customer records, developing predictive models, ETL pipelines, and executive dashboards used for risk identification, churn reduction, and performance optimization.Key contributions include reducing healthcare costs by millions through risk analytics, detecting fraudulent claims, improving preventive care engagement, and building churn prediction systems that improved customer retention. I also design scalable analytics pipelines using SQL, Python, and cloud platforms to enable real-time decision-making.Core expertise:• SQL & Python analytics for large datasets• Machine learning (Random Forest, XGBoost, Logistic Regression)• Tableau & Power BI dashboard development• ETL pipelines and data modeling• A/B testing and statistical analysis• AWS cloud analytics and scalable pipelines• Predictive analytics (risk, churn, forecasting)• Data cleaning, transformation, and feature engineeringI’m seeking Data Analyst / Business Intelligence / Product Analytics roles where analytics directly influences business strategy and measurable outcomes.

Experience

1. Data Analyst

   Optum

   Aug 2024 — Present · US

   Data Analyst — Healthcare Claims Analytics Platform• Analyzed 500K+ healthcare claims using SQL and Python to identify care gaps, utilization trends, and cost drivers• Built 20+ Tableau dashboards for clinical, finance, and leadership teams enabling KPI monitoring and decision-making• Developed predictive models (Random Forest, XGBoost) to identify high-risk members and reduce readmissions• Implemented anomaly detection to identify fraudulent billing patterns, uncovering $800K in wasteful claims• Designed A/B testing framework for outreach campaigns increasing preventive visits by 25%• Automated financial and operational reporting using Excel VBA saving 20 hours per week• Built ETL pipelines for claims, provider, and member datasets improving data reliability• Supported AWS migration enabling scalable analytics and near real-time reporting• Reduced unnecessary procedures by 15% and contributed to $2.3M cost savings

Education

• University of Wisconsin-Milwaukee

  Master's degree, Information Technology and Management

• JB Institute Of Engineering and Technology (JBIET)

  Bachelor's degree, Electrical, Electronics and Communications Engineering