Lakshmi Mounika Nadimpalli

• Collaborated with senior Analysts to automate data cleaning tasks using Pandas and NumPy, enhancing data quality and reliability about saving 14 hours per week.
• Launched Data Profiling techniques Reducing, resulting in a 14% reduction in data redundancy.
• Enhanced data accuracy by automating data cleansing processes, significantly reducing manual errors.
• Employed Data Manipulation techniques in SQL to transform raw marketing data, which improved Quality by 52%
• Developed interactive data visualizations that improved stakeholder understanding by 51%
• Assisted in A/B testing analysis to provide actionable insights, which led to 39% increase in website conversion rates.
• Utilized web analytics tools to track website performance, optimizing the interface to reduce bounce rates by 33%
• Generated standard and custom reports to provide insights into business performance.

Responsibilities:

• Conducted data cleaning, validation, and analysis of clinical trial data for Phase I-III studies, ensuring compliance with FDA and EMA guidelines.
• Collaborated with cross-functional teams to provide insights into drug efficacy and safety by analyzing clinical and adverse event data.
• Conducted exploratory data analysis (EDA) using SQL and Excel to uncover trends and outliers in patient data.
• Developed interactive dashboards for clinical trial tracking and reporting, improving team collaboration using PowerBI
• Automated reporting processes using Python reducing the time required for routine compliance reports by 30%.
• Worked on SQL queries Optimization, improving the speed of data extraction by 15%
• Maintained data integrity by setting up relevant check and measures at multiple stages of database development.
• Assisted in the design, development and implementation of database systems.
• Implemented data validation checks, increasing data accuracy and reliability by 40%
• Collaborated with senior analyst to create SQL-based reports contributing to a 15% increase in data transparency.
• Optimized existing SQL Queries, reducing report generation times by 40%
• Enhanced data collection methods, improving the accuracy of collected data by 25%