Shoiab Mohammed

Designed and maintained ETL workflows in Excel and Power BI to ingest, cleanse, and transform service data, reducing manual preparation time by ~40%. Built Power BI dashboards for equipment KPIs and applied regression/forecasting models to improve predictive maintenance scheduling and reduce unplanned downtime.

Developed Excel-based data models and dashboards to track lab equipment service schedules and failure patterns, improving scheduled-maintenance compliance. Used predictive modelling and trend analysis on procurement datasets and automated monthly performance report generation for department heads.

Conducted root cause analysis on recurring equipment failures using historical service data, identifying high-frequency failure modes to inform maintenance policy. Designed structured service-log schemas and produced monthly KPI performance summaries for cross-departmental decision-making.

Supported diagnostic equipment software troubleshooting using SQL queries and data-wrangling scripts, and produced analytics reports for lab performance monitoring. Completed certified training in GE ultrasound systems focused on data interpretation, performance benchmarking, and structured reporting.

Analyzed equipment performance data from field deployments across regions to identify failure trends and feed findings back into product service documentation.

Resolved complex customer technical issues by leveraging system data logs and diagnostic tooling, maintaining first-call resolution and SLA targets. Provided technical support based on diagnostic findings from customer systems.

Earned a Bachelor of Technology in Biomedical Engineering from Rajiv Gandhi College of Engineering & Technology between 2004 and 2008.

Completed an advanced certification program in Data Analytics covering SQL, Python, Power BI, Tableau, statistical modeling, and machine learning fundamentals.