Vipan Parajuli
Data Analyst @UnitedHealthcare
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WORK HISTORY
Data Analyst @UnitedHealthcare
At UnitedHealthcare, I analyzed claims, patient outcomes, and clinical data using SQL and Python to identify trends in healthcare utilization and optimize resource allocation. I developed healthcare cost prediction models that improved budget forecasting accuracy by 20%. I also designed interactive Tableau dashboards to track key performance metrics and automated ETL workflows with Informatica to streamline data integration. Additionally, I conducted risk stratification analysis to enhance care management strategies, utilizing Azure and Snowflake for scalable data solutions.Key Contributions-Improved budget forecasting accuracy by 20% through predictive analytics-Automated ETL processes, reducing manual data processing time by 30%-Designed Tableau dashboards to track patient care and operational efficiency-Conducted risk analysis to optimize targeted healthcare interventions-Leveraged cloud-based data solutions (Azure, Snowflake) for scalable reporting.
EDUCATION
McNeese State University
Bachelor's degree
ABOUT VIPAN PARAJULI
I am a highly skilled Data Analyst with 3+ years of experience in analyzing complex datasets and delivering actionable insights to optimize business processes. My expertise spans across advanced analytics, predictive modeling, and data visualization using tools like SQL, Python, R, Tableau, and Power BI. I specialize in automating data workflows, streamlining ETL processes, and developing interactive dashboards to facilitate real-time decision-making.With a proven track record of collaborating with cross-functional teams, I’ve driven key business initiatives through data storytelling, predictive analytics, and A/B testing. My experience across industries such as finance, telecommunications, and healthcare has equipped me with a diverse skill set to solve complex problems and deliver measurable impact.Key Achievements-Increased budget forecasting accuracy by 20% through healthcare cost prediction models at -UnitedHealthcare-Improved ETL pipeline processing times by 40% through automation at Wells Fargo-Achieved a 30% reduction in query response times by implementing Hadoop and Spark for big data processing at T-Mobile-Drove a 15% increase in market penetration by developing predictive models for sales trends at T-Mobile.
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