About Me

I’ve spent the last few years working at the edge of logistics and platform strategy – scaling last-mile networks, leading operations, and rethinking how partner ecosystems function. But I don’t just manage workflows. I question them. And I use data to redesign them.

With a background in supply chain management and operations research, I focus on solving real-world problems through algorithms, automation, and practical experimentation. Whether it’s designing a new pricing model or mapping operational behavior into data-driven structures, I love turning complexity into clarity.

Portrait

Where I thrive

  • Building optimization models with Python, Gurobi, and Pandas
  • Prototyping decision tools using Excel and Streamlit
  • Creating data pipelines and KPI dashboards to drive insights
  • Applying operations research to pricing, routing, and planning problems
  • Designing algorithmic logic to steer partner and delivery decisions
  • Running simulations and scenario analyses in cloud environments (AWS, Azure)
  • Designing pricing models that reflect market behavior and margin goals
  • Bridging the gap between Ops and IT through hands-on requirements management and system design input.
  • Auditing, debugging, and improving data-driven processes
  • Conducting root cause analysis on performance and service quality
  • Translating business strategy into actionable operational playbooks
  • Rebuilding broken workflows into scalable, testable processes

Selected Projects

Crowdsourced Routing & Pricing Logic

Developed and tested a multi-variable pricing model for a delivery platform using Python and optimization heuristics – improving partner acquisition cost-per-order.

Intelligent Dynamic Pricing

Developed a machine learning model to optimize pricing strategies for crowdsourced logistics. By learning from historical job data and contextual features, the model recommends price ranges that balance partner activation, margin, and fulfillment rate.

Linehaul Network Simulation Tool

Designed a lightweight tool to simulate and evaluate static linehaul configurations between hubs. The tool calculates cost, lead time and capacity utilization across different network setups and supports data-driven decision-making in middle-mile planning.