Lead Data Scientist (Remote/Virtual)

US Foods•Rosemont, IL

2d•$100,000 - $160,000•Remote

About The Position

We’re excited about your interest in pursuing the next step in your career with US Foods! Your continuous growth and development is critical to our success. US Foods is committed to working with and providing reasonable accommodation to individuals with disabilities. If reasonable accommodation is needed to participate in the interview process or to perform essential job functions, please contact our US Foods Application Accommodation Line at 855-873-2468. You will be prompted to leave a message. Please state the specifics of the assistance needed and your contact information. A member of our HR department will return your call within two business days. https://www.usfoods.com/careers/job-application-accomodation.html NOTE: Before you begin your internal job search, please review the criteria you will need to start the process. The Lead Data Scientist – Commercial will lead a team of data scientists responsible for designing, developing, and deploying advanced analytics and AI solutions that drive commercial growth, seller efficiency improvements and customer engagement. This includes seller effectiveness solutions, eCommerce AI capabilities such as personalization and product recommendations, and advanced marketing and merchandising analytics. This leader owns the Commercial Advanced Analytics portfolio, with accountability for analysis, development, and implementation of AI / ML solutions and delivery of measurable business outcomes across Sales, Marketing, and Digital channels. Responsibilities span the full lifecycle of initiatives, from problem framing and solution design through production deployment and adoption. This position is remote which means the work can be completed from anywhere except Hawaii or United States Territories.

Requirements

Six years of experience or greater in advanced analytics, data science, or applied machine learning, with progressive leadership responsibility.
Experience deploying applied AI solutions on cloud platforms (e.g., AWS SageMaker and Bedrock), including LLM-based and agentic architectures, with production-grade hosting, monitoring, governance, and end-to-end MLOps.
Experience guiding teams in Python-based data science ecosystems and collaborative development practices, including code quality, testing, and reproducibility.
Comfort with modern agentic coding tools (e.g., Claude Code, GitHub Copilot).
Strong command of machine learning, optimization methods, and statistical experimentation at scale, particularly in commercial, customer, or growth-oriented use cases.
Business-oriented analytical thinker with a high bar for rigor, execution, and reliability.
Clear, concise communicator able to influence senior leaders with data-driven insights.
Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related quantitative field required.

Nice To Haves

Experience leading applied data science or AI teams in commercial, sales, marketing, or eCommerce environments (especially B2B).
Strong consultative, business-facing background with demonstrated success driving adoption of analytics products.
Able to communicate clearly and influence stakeholders through storytelling and public speaking.
Experience in complex, SKU-heavy or distribution-style businesses.
PhD in a quantitative field a plus.

Responsibilities

Partner with senior Sales, Merchandising, Marketing, and Digital stakeholders to identify, prioritize, and frame high-impact business problems suited for advanced analytics and AI.
Oversee delivery of solutions including eCommerce personalization and recommendation systems, seller effectiveness and productivity tools, and advanced marketing and merchandising analytics.
Ensure solutions are production-ready, scalable, and embedded into commercial workflows to drive sustained and measurable revenue, margin, and customer experience impact.
Lead, develop, and retain high-performing teams of data scientists, with a strong focus on innovation, execution, and talent development.
Shape and deliver the commercial analytics and AI roadmap aligned to growth priorities, customer strategy, and measurable business outcomes.
Influence decision-making by leading statistical experimentation and driving adoption of data-driven decision making across Sales, Merchandising, Marketing, and Digital leadership teams.
Provide technical and analytical leadership across applied AI, optimization, and statistical modeling.
Set standards for analytical rigor, model performance, reliability, and commercial business impact.
Collaborate with ML Engineering, Digital, and Platform teams to ensure robust code development, scalable deployment, and stable production operations across the full model lifecycle.