Sr. Data Scientist - Supply Chain

US Foods, Inc.; Des Plaines (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

Short-term and long-term disability

Employee stock purchase plan

Life insurance

Annual incentive plan bonus

Job summary

US Foods, Inc. is seeking a Sr. Data Scientist in Des Plaines, IL (remote) to lead analytics for supply chain forecasting, demand planning, buying decisions, and inventory optimization. You will build, productionalize, and deploy forecasting and optimization models with cross-functional partners.

The role emphasizes end-to-end model delivery, data sourcing, feature engineering, and mentoring junior DS team members in a scalable, cloud-enabled environment.

Qualifications

• Master’s or higher in a quantitative field with 3+ years of experience or a BA/BS with 6+ years in data science.
• Strong communication skills for cross-functional collaboration.
• Expert-level understanding of ML algorithms, evaluation metrics, and deployment considerations.

Responsibilities

• Lead forecasting, optimization, and ML model development end-to-end.
• Mentor junior data scientists and guide stakeholder communication.
• Collaborate with product management to align DS efforts with business needs.

Skills

Forecasting

Modeling

Python

SQL

ML/DL

Cloud platforms

DevOps/MLOps

NLP

Containerization

Agile/Scrum

Education

Master’s degree in data science, mathematics, computer science, statistics, or related

Bachelor’s degree with 6+ years of experience in data science

Tools

Gurobi

Pyomo

PuLP

Job description

US Foods, Inc. is hiring a Sr. Data Scientist to lead analytics initiatives that support supply chain forecasting, demand planning, buying decisions, and inventory optimization. This role in Des Plaines, IL (remote) focuses on building and productionalizing forecasting and optimization models, working closely with cross-functional stakeholders, and guiding model delivery from initial development through implementation.

Key Responsibilities

• Partner with Associate Data Scientists and Data Scientists on data sourcing, data cleansing, feature engineering, and baseline model creation.
• Independently lead formulation and development of forecasting, optimization, and machine learning models while managing multiple model development projects.
• Design, implement, and improve advanced machine learning and deep learning models to address large-scale, real-world supply chain demand, buying, inventory, and replenishment challenges.
• Collaborate with cross-functional stakeholders, including product management, to maintain tight alignment between data science efforts and business needs.
• Own model development end-to-end, including the machine learning pipeline, documentation, model drift, and remodeling strategy.
• Mentor Associate Data Scientists and Data Scientists by sharing data science knowledge and supporting effective stakeholder communication.
• Coordinate with the ML team to anticipate deployment issues, define resource requirements, and support successful deployment and retraining.
• Take and delegate ownership of critical tickets or issues assigned by the Lead Data Scientist or Director of Data Science.
• Independently navigate an extensive codebase, with a focus on troubleshooting, debugging, and code improvements.
• Contribute to coding standards and coding conventions, proactively reinforcing sound coding practices across the data science team.
• Create and maintain documentation for ML models, data sources, and methodology.
• Support feasibility document creation.
• Participate in core team processes, including R&D, recommending and implementing process improvements or new methodologies.
• Share knowledge through presentations at periodic internal team sessions and workshops.
• Guide use of development methodologies such as Scrum and Kanban, assisting with group project execution including features, tasks, effort estimates, and timing.

Required Qualifications

• Master’s degree in data science, mathematics, computer science, statistics, or a related field with 3+ years of experience; or a Bachelor’s degree with 6+ years of experience in data science.
• Strong written, verbal, and interpersonal communication skills, including the ability to work with team members and cross-functional partners.
• Expert-level understanding of classification, regression, clustering, dimensionality reduction, association rule learning, ensemble methods (Random Forests), boosting (AdaBoost, Gradient Boosting), neural networks and deep learning, model evaluation and metrics, cross-validation, hyperparameter tuning, optimization algorithms, and NLP.
• Working knowledge of Agile/Scrum, with 1-2 years of experience and practical understanding of relevant epics, features, tasks, and effort.
• Intellectual curiosity to investigate recent developments in the field, including LLM and Generative AI models.
• Ability to anticipate deployment limitations, data latency, appropriate algorithm selection, and mathematical assumptions.
• At least 1+ years working with a major cloud platform, using ML frameworks from data exploration to deployment.
• Working knowledge of handling large datasets in a cloud environment.
• Working knowledge of APIs and CI/CD (Continuous Integration/Continuous Deployment).
• Understanding of DevOps and MLOps principles.
• 1+ years writing production-grade code in scripting languages including Bash, Python, and SQL, with experience improving code structure, selecting data structures, optimizing performance, and writing custom code for unique situations.
• Proven ability to independently navigate a data lake environment to create training datasets or feature stores.
• Experience creating, deploying, and troubleshooting containers in the context of ML modeling.
• 1+ years experience with version control concepts and systems such as Git.
• Ability to research ML frameworks/algorithms, datasets, and feature stores and contribute to solving data science problems.
• Ability to provide macro-level thought leadership to junior team members regarding best practices, issues, causes, and resolutions.

Preferred Qualifications

• 2 years of supply chain analytics experience, preferably related to replenishment systems, time series forecasting, order optimization, network optimization, inventory management, and/or logistics.
• Preferred 1+ year of Optimization & Operations Research experience, including writing production-grade code in optimization modeling languages such as Gurobi, Pyomo, or PuLP.

Technologies

• Python, SQL, Bash, Git
• CI/CD (Continuous Integration/Continuous Deployment), Agile, Scrum, Kanban
• DevOps, MLOps
• Random Forests, AdaBoost, Gradient Boosting, Neural Networks, Deep Learning, NLP
• LLM/Generative AI models
• Gurobi, Pyomo, PuLP

Compensation & Benefits

• Salary range: USD 100,000 - 155,000 per year
• Health insurance
• Pre-tax spending accounts
• Retirement benefits
• Paid time off
• Short-term and long-term disability
• Employee stock purchase plan
• Life insurance
• Annual incentive plan bonus may be available for this role
• Compensation depends on relevant experience and/or education, specific skills, function, geographic location, and other factors as applicable by law

Team Relationships

Works with Associate Data Scientists, Data Scientists, Lead Data Scientists, Principal Data Scientists, and the Director of DS.