Sindhu Simgamsetty

1.Conducted statistical analysis of large data sets to identify trends and formulate predictive insights.
2.Analyzed diverse spreadsheets, revealing variations in data tracking methodologies.
Ensured data integrity through rigorous validation and reconciliation processes.
3.Recommended improvements to data tracking methodologies and reporting processes for enhanced efficiency.
4.Designed and built visualizations using structured and unstructured data sets.
5.Created research reports utilizing credible qualitative and quantitative methodologies based on key findings.

1. Analyzing data using statistical techniques and providing reports
2.Developing and implementing databases and data collection systems
3. Acquiring data from primary and secondary sources and maintaining data systems
4. Identifying, analyzing, and interpreting trends or patterns in complex data sets
5. Filter Data by reviewing reports and performance indicators to identify and correct
code problems.
6. Design, build, and maintain data warehouses, data lakes, and ETL pipelines

7. Optimize existing data infrastructure for performance and scalability
8.Rearchitect systems to improve efficiency and reliability
9.Collaborate with stakeholders to understand data requirements and develop solutions
10. Implement best practices for data management and governance
11. Troubleshoot and resolve issues related to data processing and storage
12. Document processes, workflows, and data models
13. Working with management to prioritize business and information needs
14. Locating and defining new process improvement opportunities