• Led analytics projects, integrating Microsoft Excel, Python, NumPy, Power BI, and SQL to drive data-driven decisions.• Employed NLP (NLTK) techniques for advanced text analytics and sentiment analysis in healthcare data.• Utilized MicroStrategy and Tableau for effective data visualization and reporting.• Managed data workflows using Confluence, enhancing team collaboration and project management.• Orchestrated data integration and warehousing using Azure Data Bricks and Snowflake.• Advanced statistical models such as survival analysis and propensity score matching is essential for analyzing healthcare data, ensuring accurate outcome assessment and accounting for confounding variables.• Implemented Azure ADLS for efficient data storage and access in cloud environments.• Developed predictive models using R Programming, enhancing patient outcome predictions.• Conducted thorough data cleaning and transformation with Open Refine.• Leveraged IBM SPSS for statistical analysis and hypothesis testing.• Longitudinal data analysis techniques and machine learning models enable healthcare data analysts to uncover temporal trends, predict patient outcomes, and provide personalized clinical decision support, enhancing healthcare delivery.• Optimized data storage and retrieval processes using Microsoft Access.• Administered secure data transfers and storage with AWS S3.• Designed and maintained dashboards using Power BI, providing real-time insights.• Ensured data integrity and consistency using advanced SQL techniques.• Automated data processing tasks with Python scripts, improving efficiency.• Conducted advanced data analysis with NumPy, extracting key patterns and trends.• Collaborated with cross-functional teams to align data analytics with business goals.

• Developed data visualizations using Google Charts, Tableau, and Grafana for insightful insurance analytics.• Utilized Chartist and Fusion Charts for custom data visualization solutions.• Implemented Data wrapper and Infogram for interactive reporting.• Integrated Chart Blocks for dynamic chart creation in insurance reports.• Managed AWS Redshift databases for robust data warehousing solutions.• Advanced statistical models inform the development of dynamic and interactive data visualizations, facilitating insightful exploration of complex data relationships and patterns.• Administered AWS S3 for efficient data storage and retrieval.• Automated data processing and analysis tasks with Python.• Utilized R for statistical analysis and predictive modeling in insurance.• Ensured high data quality and integrity using SQL.• Collaborated with business stakeholders to align data analytics with strategic goals.• Streamlined data workflows using Confluence for enhanced project management.• Developed and maintained insightful dashboards using Tableau.• Leveraged advanced SQL techniques for data extraction and analysis.• Facilitated team collaboration and data sharing with Confluence.

Leveraged DAX Studio for advanced data analysis and modeling in marketing.• Utilized ALM Toolkit for efficient lifecycle management of analytics projects.• Employed Tabular Editor for enhanced data modeling and analysis.• Implemented Metadata Translator for effective data mapping and integration.• Conducted data warehousing and modeling for targeted advertising strategies.• Utilized Python for data manipulation and analysis in marketing campaigns.• Managed Open-source tools for cost-effective data analytics solutions.• Collaborated with marketing teams to align data-driven insights with campaign goals.• Developed dynamic dashboards and reports using Power BI.• Streamlined data integration processes for efficient marketing analytics.• Ensured data accuracy and consistency using advanced SQL techniques.• Automated routine data processing tasks, enhancing operational efficiency.

• Tableau tools for dashboard creation, charts, and report generation.• Utilized Tableau Desktop and Public for sharing visualizations and reports.• Employed Tableau Online, Server, and Reader for efficient data sharing.• Managed Microsoft Mastered SQL Server databases for robust data storage.• Automated data processing tasks using Python and R.• Leveraged Apache Hive for handling large datasets.• Integrated Power BI for dynamic data visualization and reporting.• Utilized Git for version control in analytics projects.• Implemented Jenkins for continuous integration and deployment.• Collaborated with IT teams to align data analytics with business objectives.• Developed insightful dashboards and reports using Tableau.• Ensured data quality and integrity using SQL.

• Utilized MySQL and PostgreSQL for database management and optimization.• Employed Talend for data integration and ETL processes.• Leveraged Python for scripting and data manipulation tasks.• Managed Amazon Redshift databases for data warehousing.• Utilized Subversion (SVN) for version control.• Developed data visualization solutions using QlikView.• Implemented Docker for containerization of applications.• Streamlined SQL development processes for efficient data handling.