Developed a software fix for data analysis, resulting in an 18% increase in project efficiency by rectifying erroneous data identification.Created separate functions for data analysis and extraction within the software product, integrated into corporate operations, resulting in an increase in the volume of processed tasks from 8.7 million to 11.3 million per day.Developed a model and protocol for testing corporate equipment functionality. Leveraging Python, successfully debugged numerous minor bugs that occasionally occurred in operation, resulting in a decrease in downtime from 18% to 7% overall.Optimized task processing speed, resulting in freeing up corporate resources for developing third-party projects focused on automating data processing and building resulting models tailored to client requirements.Implemented Continuous Integration / Continuous Deployment (CI/CD) methodology to accelerate the software development cycle and enhance the quality of released products.Conducted research and developed new algorithms for data analysis, resulting in a 13% increase in forecasting accuracy and improved customer satisfaction levels.Implemented an automated data backup system, ensuring reliable data preservation and reducing data loss risks by 43%.Optimized the software testing process, reducing testing time by 15% and decreasing the number of errors in the final product.Managed data processing software handlers, leveraging knowledge of multiple languages.