Harsha Vardhan Bolla

• Specialize in production support, ensuring seamless operation of Micro Focus environments.
• Proficient in COBOL, PL/SQL, VSAM, DB2, Flat Files, JCL, Unix/Linux, SQL, and IBM Workload Scheduler.
• Monitor server ecosystems and batch jobs using ESMAC PBBATCH to ensure optimal performance and quick issue resolution.
• Manage incident resolution through the ServiceNow ticketing system, consistently meeting or exceeding SLAs.
• Act as a vital bridge between operations and development teams, fostering effective communication to swiftly address errors and minimize business process impacts.
• Implement corrective actions and develop preventive strategies to improve system reliability and performance handling database management with DB2 and Oracle SQL.
• Develop customized scripts and implement structured methodologies and quality assurance.
• Collaborate with cross-functional teams to implement machine learning models for predictive analytics.
• Conduct research to identify industry trends and emerging technologies, driving innovation in support processes.

Ticket Handling: Efficiently manage both CR (Change Request) and IR (Issue Resolution) tickets, prioritizing based on criticality and client requirements.
Change Request Management: Handle CR tickets, which involve addressing new client requirements. This includes writing new programs from scratch or enhancing existing code to meet client specifications.
Issue Resolution: Address IR tickets, which involve resolving issues in client applications. These issues can be related to data updates or bug fixes, and they are resolved promptly to ensure client satisfaction.
Client Collaboration: Foster effective communication with clients by sharing prototype designs and seeking their feedback and approval. Collaborate with project managers to ensure alignment with client expectations.
Unit Testing: Conduct thorough unit testing to ensure the developed code functions correctly and efficiently. Prepare test documents and cases for validation.
Testing Support: Provide support to the testing team during User Acceptance Testing (UAT) and Regression Testing phases. Address any issues or bugs that arise during testing promptly.

• Built predictive and decision models using machine learning algorithms for various business study cases.
• Analyzed large and imbalanced datasets to provide data insights and strategic directions.
• Developed customized scripts for data scraping from multiple websites.
• Worked with text data using text mining techniques for extraction, cleaning, and categorization.
• Assisted in data collection, cleaning, and analysis, contributing to data-driven insights.
• Participated in data visualization efforts using Tableau.
• Conducted research to identify industry trends and best practices in data science.

Projects :
Incident Impact Prediction:
Predicted the impact of incidents raised by customers using a random forest classification algorithm.
Analyzed and understood technical details, performed EDA using Python, and led team meetings.
Achieved 97% accuracy with an F1-score of 98% using data upsampling techniques on a dataset of 141K records with 36 features.
Deployed the model using Streamlit and presented overall model interpretations and reports.

Email Template Generator:
Developed web scrapers with Beautiful Soup to collect email templates from online sources.
Performed text processing, including cleaning and duplication removal, using NLTK library.
Generated template effectiveness based on keywords and shared findings with the team.
Deployed the model using Streamlit.