Selected work

Forecasts, decisions,
and production delivery.

Examples from my work in global shipping: improving container movement forecasts, reducing operating costs, and delivering internal tools on Google Cloud.

Work / 01

More accurate container forecasts

  • Time series
  • Applied ML
  • Operational planning
Problem
Container movement forecasts support network and operational planning under changing demand.
Contribution
Developing forecasting workflows, validating predictions, and connecting model outputs to planning needs.
Outcome
Improved container movement forecast accuracy to support operational planning in global shipping.
Work / 02

Lower operating costs

  • Optimization
  • Simulation
  • Decision science
Problem
Operational planning needs to balance movement costs, network constraints, and business requirements.
Contribution
Translating planning requirements into optimization objectives, constraints, and scenario comparisons with business teams.
Outcome
Reduced operating costs through optimization and decision-support work for complex shipping operations.
Work / 03

Internal tools, deployed on GCP

  • Production systems
  • Cloud analytics
  • Technical leadership
Problem
Forecasting and optimization work needs repeatable data workflows and usable outputs for internal teams.
Contribution
Delivering internal data science tools end to end on GCP, connecting data workflows, models, validation, and production deployment.
Outcome
Delivered internal data science tools end to end on Google Cloud, connecting modeling with production deployment.

Connecting models to operations.

My work combines analytical problem formulation, production delivery, and technical leadership. I collaborate across operations, planning, and engineering, and lead six data scientists at Ocean Network Express.

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