MUHAMMAD BAQIR

Developed Python and TensorFlow forecasting models on AWS and Azure reducing inventory shortages by 20 percent across 200 plus items Optimized cloud resources and operations reducing infrastructure costs by 18 percent Improved Jira and ServiceNow ticket routing increasing first call resolution from 61 percent to 84 percent Automated 20 percent of repetitive tasks using CI CD pipelines and deployment scripts Implemented Nagios and Zabbix monitoring during AWS migration reducing system downtime by 35 percent

Improved troubleshooting time through standardized operational runbooks and root cause analysis documentation. Reduced recurring infrastructure failures by 20 percent through proactive procedures and monitoring. Built data pipelines for 20 plus enterprise systems and centralized monitoring using Prometheus Grafana and Azure Monitor. Managed 15 plus network environments including DNS VPN firewalls TLS Cisco and Juniper infrastructure. Supported troubleshooting and operational maintenance of network systems.

Core Focus: Distributed systems, cloud architecture, microservices, and network protocols. Key Coursework: Advanced software engineering, communication networks, system performance modeling, and distributed algorithms. Hands-on Skills: Building scalable microservices, containerized deployments, and automated testing pipelines.

ore Focus: Computer networking, routing protocols, operating systems, and backend software engineering. Key Coursework: Data structures and algorithms, database management, network security, and hardware design. Hands-on Skills: Network infrastructure setup, Linux administration, and system-level programming.