Amitesh Singh

• Created real-time freight intelligence dashboards by integrating external market feeds into Power BI using automated data collection.
• Automated pricing data extraction and updates from 5+ global market sources using Python (Pandas, Beautiful Soup), integrating
outputs into Excel dashboards.
• Integrated pricing outputs into Excel dashboards to improve market responsiveness and efficiency by 30% across trading operations.
• Developed Power BI dashboards tracking daily refinery margins and crack spreads across gasoline, diesel, and jet fuel products.
• Enabled $5M+ in quarterly savings by building Excel pricing models to calculate break-even prices for fuel products across markets.
• Helped traders assess discounting thresholds and strengthen negotiation positions through comprehensive pricing analysis and
modeling techniques.
• Improved shipping cost accuracy by 20%+ through SQL-based extraction and analysis of 5 years of freight data.
• Conducted freight forecasting using Python regression models analyzing 10+ macroeconomic indicators across global trading routes.
• Enhanced logistics planning across China, Taiwan, and Rest of World markets through freight optimization modeling techniques .
• Tracked seasonal demand patterns for heating oil and gasoline using 7 years of historical data for inventory planning.
• Led inventory optimization planning for 6+ raw material categories by analyzing technical specifications and demand patterns .
• Improved forecasting accuracy and reduced operational losses by $4M/month through data analytics and decision-making processes.
• Conducted feasibility analysis using specialized modeling software to evaluate 100+ raw material combinations through detailed
scenario planning, informing strategic procurement decisions and supporting multi-month operational planning horizons.
• Supported crude oil blending optimization by analyzing API gravity and sulfur content specifications across multiple supply s ources.

• Automated compliance monitoring using Python-based anomaly detection models, delivering $1.6M in cost savings across
procurement operations.
• Analyzed 175K+ transaction records with clustering algorithms to identify $3.4M+ in procurement cost optimization opportunities
annually.
• Built 4 interactive Tableau dashboards providing real-time spending analytics and vendor performance insights for 300+ users.
• Detected irregular spending patterns, vendor duplications, and process inefficiencies through advanced data mining and analysis
techniques.
• Extracted operational data using SQL to track KPIs and built Tableau dashboards for weekly variance analysis.
• Identified 8% operational deviations through comprehensive benchmark comparisons and performance monitoring across
manufacturing processes and systems.
• Led a team of 3 engineers to streamline interdepartmental data pipelines using Google BigQuery and SQL.
• Improved data reliability across plant operations by eliminating 5+ manual handoffs and reducing reporting time by 30%.
• Developed Excel-based cost models that reduced variance between projected and actual costs to within 20% accuracy.
• Enhanced data-driven procurement decisions through comprehensive vendor performance tracking and real-time compliance
monitoring systems.