Remote Senior Data Scientist, Supply Chain Forecasting

US Foods; Illinois City (IL); Remote; USD 100,000 - 155,000; Full time

Benefits offered by this job

Health insurance

Pre‑tax spending accounts

Retirement benefits

Paid time off

Disability insurance

Employee stock purchase plan

Life insurance

Job summary

US Foods is seeking a Sr Data Scientist for remote work across the United States (excluding Hawaii and territories). The role focuses on time series forecasting, demand planning, and inventory optimization using advanced ML and optimization techniques to balance costs and service levels.

The successful candidate will lead model development, collaborate with data teams, and mentor junior staff while driving deployment and maintenance of end-to-end ML pipelines in a data‑driven supply chain

Qualifications

• Master’s or equivalent mix of education and experience in data science.
• Strong communication with cross-functional teams and stakeholders.
• Expert understanding of ML, optimization, and evaluation metrics.
• Experience with Agile/Scrum and cloud-based ML pipelines.
• Ability to navigate data lakes and feature stores.

Responsibilities

• Lead forecasting, optimization, and ML model development across supply chain domains.
• Collaborate with cross‑functional teams to translate business challenges into ML problems.
• Own model development lifecycle from data exploration to deployment.
• Mentor junior data scientists and ensure coding standards.
• Document models, data sources, and methodologies; support R&D and process improvements.

Skills

Time series forecasting

ML/Optimization modeling

Statistical analysis

Experimentation & baselining

Communication with stakeholders

Education

Master’s degree in data science, mathematics, CS, or statistics

Bachelor’s degree + 6+ years experience

Tools

Python

SQL

Bash

Job description

US Foods is seeking a Sr Data Scientist for remote work across the United States (excluding Hawaii and territories). The role focuses on time series forecasting, demand planning, and inventory optimization using advanced ML and optimization techniques to balance costs and service levels.

The successful candidate will lead model development, collaborate with data teams, and mentor junior staff while driving deployment and maintenance of end-to-end ML pipelines in a data‑driven supply chain