Staff Data Scientist - Network
Core
Technical anchor for Demand Forecasting, building models to predict parcel volume, size, weight, and inbound international flows to optimize logistics network efficiency.
Role type
Staff Data Scientist (hands-on IC)
Builds
Integrated demand forecasts and physical volume models for sortation, middle-mile, and last-mile operations.
Domain
Logistics / Time-series forecasting / Operations Research
Deliverable
production ML models
Required skills
Time-series forecasting, Python, SQL, Gradient Boosting, Deep Learning, Feature Engineering, Model Validation, System Design, Stakeholder Communication
Preferred skills
Classical statistical approaches, AI tools (LLMs, code assistants), Operational impact quantification
Technologies
Python, SQL, Gradient Boosting, Deep Learning
Responsibilities
Own the integrated forecast end-to-end from live tracking to model-generated long-horizon predictions; Build high-leverage models for inbound international volume and parcel size/weight; Set methodology and validation standards for the forecasting area; Define interfaces between forecasting models and downstream demand management/routing systems; Mentor Senior Data Scientists and Analysts on technical approach; Monitor production model quality and drift; Quantify model error impact on cost per parcel.
Seniority
Staff, hands-on IC with technical leadership
