Prajwal Uday

Analyzed ground operations data in Python to improve fleet resource utilization by 8 percent and support operational decision making.
Ran 1000 Monte Carlo simulations to measure uncertainty and forecast delays, and reduce operational risk by 15 percent and evaluate resource needs.
Built predictive models on sensor data to support maintenance planning and improve forecast accuracy by 5 percent for business decisions.
Automated time series and analysis workflows in Python, which reduced analysis error from 12 percent to 3 percent.
Worked with cross functional teams and department heads to turn model results into practical maintenance strategies.
Built reporting insights on maintenance scheduling and resource allocation to support business and operational decision making.

Analyzed ground operations data in Python to improve fleet resource utilization by 8 percent and support operational decision making., Ran 1000 Monte Carlo simulations to measure uncertainty and forecast delays, and reduce operational risk by 15 percent and evaluate resource needs., Built predictive models on sensor data to support maintenance planning and improve forecast accuracy by 5 percent for business decisions., Automated time series and analysis workflows in Python, which reduced analysis error from 12 percent to 3 percent., Worked with cross functional teams and department heads to turn model results into practical maintenance strategies., Built reporting insights on maintenance scheduling and resource allocation to support business and operational decision making.

Built a data cleaning pipeline for large-scale environmental datasets (metrics of 50000 saplings), ensuring high data integrity for analysis.
Improved data assessment accuracy by 9 times by applying statistical validation methods to quality-check over 50000+ data points.

Built a data cleaning pipeline for large-scale environmental datasets (metrics of 50000 saplings), ensuring high data integrity for analysis., Improved data assessment accuracy by 9 times by applying statistical validation methods to quality-check over 50000+ data points.

Led a cross functional student team of 20 members and managed timelines, resources, and project deliverables for international competitions.
Managed budgets and procurement planning to make sure key resources were available on time and within cost limits.
Reported KPIs and technical progress to sponsors and external stakeholders, which helped secure continued funding and support.

Led a cross functional student team of 20 members and managed timelines, resources, and project deliverables for international competitions., Managed budgets and procurement planning to make sure key resources were available on time and within cost limits., Reported KPIs and technical progress to sponsors and external stakeholders, which helped secure continued funding and support.