Drashti Thummar Email & Phone Number

United States

Delaware, United States

- Analyzing financial and operational data to identify trends and provide actionable insights for revenue optimization and cost management.- Developing predictive models to forecast demand, occupancy rates, and financial performance using Python, R, and machine learning techniques.- Creating interactive dashboards and reports using Tableau, Power BI, and Excel to support data-driven decision-making for cross-functional teams.- Monitoring and managing accounts, ensuring the accuracy of financial transactions, variance analysis, and compliance with industry standards.- Collaborating with marketing and revenue teams to evaluate campaign performance and customer retention strategies through data analytics.- Automating data workflows and reporting processes to increase efficiency using tools like SQL, ETL pipelines, and Python scripting.

United States

• Engineered comprehensive data cleaning protocols using Python libraries such as Pandas and NumPy, enhancing data integrity for 500,000+ records and ensuring reliable insights for subsequent analysis across departments. • Prepared and executed a comprehensive quality assurance plan for validating and processing data from source systems, resulting in a 99% accuracy rate of integrated data into the data warehouse.• Applied End-to-end solution for hosting the web application on AWS cloud with integration into S3 buckets. • Spearheaded the optimization of existing ETL workflows, reducing data load times by 60% and enhancing overall system performance, which improved the user experience for over 100 data analysts. • Executed data cleansing and transformation processes on a dataset containing 250,000 entries, improving data quality by eliminating 95% of duplicates, which resulted in more accurate reporting and analysis for stakeholders. • Composed Spark tuning and optimization techniques to increase data processing efficiency by 70%.

India

Engineered backend systems and ETL pipelines with Python and Scala, improving data processing efficiency and reducing system latency across enterprise applications.Deployed containerized applications using Docker and Kubernetes, enhancing scalability and operational efficiency for cloud-hosted solutions.Collaborated closely with product managers and UX designers to develop user-friendly interfaces and backend services, resulting in a 20% increase in user satisfaction.Utilized Apache Spark and Hadoop ecosystems to manage large-scale data imports and transformations, supporting real-time data analysis and reporting.I have made significant contributions to database efficiency and performance, standardizing, and implementing functions and procedures in MySQL, resulting in a 25% increase in data processing efficiency and a 20% boost in overall database performance. I have also delved into exploratory data analysis, leveraging statistical methodologies to extract valuable insights into customer behavior and market trends. Utilizing machine learning algorithms, I have developed predictive models for sales forecasting and identifying potential business opportunities.

Master Of Science - Ms, Engineering Science Data Science, 3.78

Bachelor Of Engineering - Be, Computer Science, 3.8