Remote Senior Data Scientist - Supply Chain Forecasting

US Foods; Illinois; Remote; USD 100,000 - 155,000; Full time

Benefits offered by this job

Health insurance

Employee stock purchase plan

Retirement benefits

Paid time off

Job summary

US Foods is seeking a Sr Data Scientist – Supply Chain to lead advanced analytics across time series forecasting, demand planning, buying and inventory optimization. You will develop production-ready forecasting and optimization models and collaborate with cross-functional teams to translate business challenges into data-driven solutions.

Ideal candidates have mastery in time series, ML/optimization, cloud and MLOps, with 3+ years of experience in data science and a relevant advanced degree.

Qualifications

• Master’s degree in data science, mathematics, CS or statistics.
• 3+ years of data science experience or 6+ years with a Bachelor’s.
• Expertise in time series forecasting, optimization and ML methods.
• Experience with cloud platforms and DevOps/MLOps practices.
• Proficient in Python, SQL and data modeling.

Responsibilities

• Lead forecasting, optimization, and ML model development from ideation to deployment.
• Collaborate with cross-functional stakeholders including product owners.
• Create and maintain ML pipelines, documentation and model drift strategies.
• Mentor junior data scientists and contribute to coding standards.
• Navigate large data lakes and containerized ML environments.

Skills

Time series forecasting

Optimization

Machine learning

Deep learning

Python

SQL

Cloud platforms

DevOps / MLOps

Data storytelling

Scrum / Agile

Education

Master’s degree in data science / math / CS

Bachelor’s degree + 6+ years

Tools

Gurobi

Pyomo

PuLP

TensorFlow / PyTorch

Job description

US Foods is seeking a Sr Data Scientist – Supply Chain to lead advanced analytics across time series forecasting, demand planning, buying and inventory optimization. You will develop production-ready forecasting and optimization models and collaborate with cross-functional teams to translate business challenges into data-driven solutions.

Ideal candidates have mastery in time series, ML/optimization, cloud and MLOps, with 3+ years of experience in data science and a relevant advanced degree.