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Sr Data Scientist (remote)

US Foods · Rosemont, IL · $100,000–$155,000 a year · Full time

Posted Sep 28, 2026 · We last checked this listing on Oct 6, 2026

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Likely interview questions for this role

Written from this job description, not a generic list. Each one notes what the interviewer is really checking.

About your past

Tell me about a model you put into production. What broke after launch and how did you find out?

What they are checking: Whether they have real experience with deployed ML, including monitoring, drift and the gap between offline and live results.

How do you explain a model's tradeoffs to a sales or operations leader who has no statistics background?

What they are checking: Whether they can present iteratively in plain terms so stakeholders trust and actually use the work.

Tell me about how you've coached junior data scientists through feature engineering and baseline models.

What they are checking: Whether they can develop others, since the role may have direct reports and kickstarts their foundational work.

What would you do

An associate data scientist shows you a model with great accuracy. What questions do you ask before you believe it?

What they are checking: Whether they check for leakage, the right baseline and evaluation that matches how the model will be used.

A stakeholder wants results in two weeks, but the data needs a month of cleanup. What do you do?

What they are checking: Whether they can scope a useful first version and be honest about limits instead of overpromising.

About the work

Walk me through how you turn a vague business request into a well-defined machine learning problem.

What they are checking: Whether they ask about the decision being made and how success is measured before choosing a model.

What goes into a model feasibility document, and when have you recommended not building a model at all?

What they are checking: Whether they judge feasibility honestly, including data quality and value, rather than building because they can.

How would you approach forecasting demand for thousands of products across many distribution centers?

What they are checking: Whether they can think about hierarchy, sparse items, seasonality and the business cost of forecast errors.

When would you choose a simple regression over a gradient boosted model, even if the boosted model scores better?

What they are checking: Whether they weigh interpretability, maintenance and stability against small gains in accuracy.

Explain how you would design an experiment to test whether a new pricing recommendation actually lifts margin.

What they are checking: Whether they understand randomization, contamination between customers and the right metric to measure.

Practice this interview out loud.

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The full job description

As published by US Foods.

ARE YOU A CURRENT US FOODS EMPLOYEE? PLEASE APPLY DIRECTLY THROUGH OUR INTERNAL WORKDAY CAREER SITE Join Our Community of Food People! The Sr Data Scientist executes statistical and mathematical analyses to support business decision-making. This role supports artificial intelligence/machine learning (AI/ML) in a deployed production environment. They are experts in the field of Data Science. Consequently, the Sr Data Scientist proactively works with cross-functional teams to seek and understand the business/domain context of potential problems that may be solved using ML. They present data science solutions to stakeholders in an iterative fashion. The Sr. Data Scientist works with Associate Data Scientists and Data Scientists in converting a business problem into an ML problem and kickstarting foundational work including data exploration, feature engineering, basic hypothesis testing, and creation of baseline models. They create the model feasibility document in close collaboration with the Data Scientists and Sr Data Scientists. The Sr Data Scientist may have direct reports including Associate Data Scientists and Data Scientists. The work for the Sr Data Scientist position is completely remote anywhere in the United States except Hawaii or United States Territories. RESPONSIBILITIES As a Sr Data Scientist, you will be expected to: • Work with Associate Data Scientists and Data Scientists in researching data sources, data cleansing, feature engineering, and creating baseline models • Independently manage multiple data science model development/projects • Collaborate and engage with various cross-functional stakeholders to ensure close coordination between data science and business stakeholders including the product management team • Provide full ownership of the model development from inception to implementation including the machine learning pipeline, documentation, model drift, and remodeling strategy • Mentor the Associate Data Scientists and Data Scientists in data science knowledge and their interactions with other stakeholders • Coordinate with the ML team, anticipating deployment issues upfront, setting the stage for resource requirements, and ensuring the success of model deployment and retraining • Take and delegate ownership of critical tickets or issues faced by business stakeholders as assigned by the Lead Data Scientist or Director of Data Science • Read and independently navigate through extensive codebase with a focus on troubleshooting, debugging, and/or improvement of code • Contribute to coding standards and coding conventions and proactively participate in enforcing sound coding practices across the data science team • Create and maintain documentation of the ML models, data sources, and methodology • Assist in the creation of feasibility documents • Proactively participate in the core team processes including R&D, recommending, and implementing process improvements or new methodologies • Share knowledge with other various teams and members by presentation at periodic internal team sessions/workshops • Guide usage of development methodologies (Scrum, Kanban, etc.) and assist in their implementation in the group projects by deciphering details including features, tasks, estimates of efforts and timing, etc. SUPERVISION : • N/A RELATIONSHIPS • Internal: Associate Data Scientists, Data Scientists, Lead Data Scientists, Principal Data Scientists, and Director of DS. WORK ENVIRONMENT • Remote MINIMUM QUALIFICATIONS As a Sr. Data Scientist, you have: • Master’s degree in data science/mathematics/CS/statistics or similar field and 3+ years of experience OR Bachelor's degree and 6+ years of experience in data science • Effective written, verbal, and interpersonal communication skills, with the ability to work and communicate effectively with team members and cross-functional teams • An expert-level understanding of the following topics: • Classification, Regression, Clustering, Dimensionality reduction, Association rule learning, Bagging (e.g., Random Forests), Boosting (e.g., AdaBoost, Gradient Boosting), Neural Networks and Deep Learning, Model Evaluation and Metrics, Cross-validation, Hyperparameter Tuning, Optimization Algorithms, NLP and more • Working knowledge of Agile/SCRUM methodologies with 1-2 years of experience and a practical understanding of the epics, features, and tasks that may be most relevant and how much effort is required for them • Sufficient intellectual curiosity to investigate the latest developments in the field (for example LLM/Generative AI models) • Ability to see the big picture and anticipate issues in terms of deployment limitations, data latency, appropriateness of a particular implementation of algorithms, and mathematical details/assumptions • At least 1+ years of working with a major cloud platform, creating ML models using frameworks from data exploration to deployment • Working knowledge in handling large datasets in a cloud environment • Working knowledge of how APIs work, CI/CD (Continuous Integration/Continuous Deployment) • Understanding of DevOps and MLOps principles • 1+ years of writing production-grade code in scripting languages including Bash, Python, and SQL with the ability to identify the areas of improvement, optimal choice of data structures, optimization of the code, and creating custom code to address unique situations • Proven, independent ability to navigate a data lake environment while creating training datasets or feature stores • Effective skills in creating, deploying, and troubleshooting containers in the context of ML modeling • 1+ years of experience with version control systems/concepts, such as Git, for tracking changes in machine learning projects • Ability to investigate/research ML frameworks/algorithms, datasets, feature stores, and contribute to solving data science problems • Capability of providing macro-level thought leadership to the junior members including the Data Scientists regarding best practices, issues, causes, and respective resolutions of those issues This role may also receive annual incentive plan bonus. ​ ​Benefits for this role may include health insurance, pre-tax spending accounts, retirement benefits, paid time off, short-term and long-term disability, employee stock purchase plan, and life insurance. To review available benefits, please click here: https://www.usfoods.com/careers/benefits.html . Compensation depends on relevant experience and/or education, specific skills, function, geographic location, and other factors as applicable by law (for example: state or local minimum wage thresholds). The expected base rate for this role is between $100,000 - $155,000 ***EOE – Race/Color/Religion/Sex/Sexual Orientation/Gender Identity/National Origin/ Age/Genetic Information /Protected Veteran/Disability Status***

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