Parth Z Email and Phone Number

• Enhanced reliability and accuracy by 15% through the engineering and maintenance of ETL pipelines and infrastructure enhancements, enabling the daily processing of 500 million data points• Achieved a 25% increase in client enrollments by utilizing Python and SQL for in-depth analysis of intricate datasets, uncovering trends and insights, and identifying crucial gaps in privacy content and product offerings• Increased query performance by 50% and reduced downtime by 20% through spearheading the maintenance and performance enhancements of SQL server environment, managing over 100 TB of data• Led the cross functional collaboration as a Subject Matter Expert for the analytics team, elevating category strategy and uncovering insights into agent productivity, client satisfaction, and market trends• Created visualizations using Power BI that translated complex datasets into actionable insights for senior management, improving strategic planning and resource allocation• Improved data accessibility and decision-making speed for Client delivery and Leadership teams by 30% through the development and maintenance of Power BI data models, dashboards, and reports• Formulated data-centric strategies for service enhancement by analyzing user behavior across platforms, leading to a 15% increase in user engagement

● Supported the data collection process by gathering and entering data from various sources into cloud-based databases using AWS services such as S3 and Redshift, ensuring accurate data availability and management of over 500,000 records.● Collaborated with senior data analysts to clean and preprocess data using Python and SQL to ensure data integrity and quality. ● Actively engaged in Agile team meetings, sharing insights, ideas, and suggestions related to data analysis projects.● Generated reports and created visualizations using Tableau and other analytics tools, effectively presenting analysis findings to support data-driven decision-making. ● Developed predictive models and machine learning algorithms using data science techniques, including time series forecasting and machine learning resulting in 20% increase in accuracy. Validated models for accuracy and documented results for client deliverables.