Program Manager, Predictions & Machine Learning , NASC Flow, Labor And Tech

Role Overview

The Predictions & Machine Learning charter within the Flow, Labor & Tech (FLT) team of NA Sort Centers is looking for a Program Manager to launch and drive programs related to predictive modeling and machine learning for labor demand forecasting. Come be part of the team that enables the NASC middle mile network to process eight billion+ packages for our customers.

The Predictions charter owns two flagship products - ARES and AARP - that power demand forecasting and labor capacity predictions across the sort center network. As a Program Manager on this charter, you will have the opportunity to work closely with experienced Product Managers, Data Scientists, and ML Engineers to drive improvements in prediction accuracy, model adoption, and operational decision-making at scale.

Position Scope & Impact

As a member of the FLT Products team, you will partner with multiple stakeholders - both within NASC (Operations, PXT, Planning teams) and across associated Tech teams - to create new programs that improve the accuracy and reliability of labor demand predictions. You will collaborate with Data Scientists and ML Engineers to translate model outputs into actionable insights for operations leaders.

The main focus of this role is driving programs and efforts in the Predictions charter for the middle mile network. You will lead programs to drive Ops knowledge and adoption of prediction tools, provide reporting on model performance and accuracy improvements, and contribute to greenfield development of ML-powered prediction capabilities.

Key job responsibilities

1. Focus on improving accuracy and reliability of prediction models (ARES, AARP), enhance model performance monitoring, and eliminate forecasting errors in the labor planning process.

2. Drive greenfield development of ML-powered prediction programs and ensure all product feature requests are routed to the appropriate Product Manager.

3. Support the training and launch of new prediction tools and model features, including troubleshooting of model-related errors and data anomalies.

4. Initiate and drive programs to improve Ops knowledge and adoption of prediction products (ARES, AARP) across the NASC network.

5. Partner with Data Scientists, ML Engineers, and Ops users to research business pain points and develop use cases for improvements in prediction accuracy and model coverage.

6. Determine success metrics, build model performance dashboards, and audit prediction accuracy on a weekly basis for mature and emerging ML workstreams.

7. Develop documentation and present model performance insights, program roadmaps, and strategic recommendations to L8-level stakeholders on a regular basis.

8. Determine initiatives that will standardize, centralize, and automate prediction pipelines and model deployment processes across the network.

9. Deep dive and root-cause prediction misses using data, create metrics-driven, actionable, and sustainable solutions to improve forecast reliability.