Work / 01More accurate container forecasts
- 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 / 02Lower operating costs
- 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 / 03Internal tools, deployed on GCP
- 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.