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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.
ESSENTIAL DUTIES AND RESPONSIBILITIES
Delivery and Impact
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.
Analytical Leadership
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.
Technical Excellence
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.
SUPERVISION :
Team of five data scientists.
RELATIONSHIPS
Internal: Analytics and Data Science teams; Executive Leadership Team; Sales, Marketing, Merchandising, Digital, and Technology leaders.
External: Vendors including cloud infrastructure providers, analytics and AI solution partners, and other strategic partners.
WORK ENVIRONMENT (Select one)
Remote: This role is fully remote, and the associate is expected to perform assigned responsibilities from a home-based environment.
MINIMUM QUALIFICATIONS
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.
EDUCATION
Bachelor's degree in Computer Science, Engineering, Mathematics, or a related quantitative field required.
PhD in a quantitative field a plus.
TRAVEL REQUIREMENT
10%
CERTIFICATIONS/TRAINING
N/A
LICENSES
N/A
PREFERRED QUALIFICATIONS
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.
This role will also receive annual incentive plan bonus up to 25% of base salary.?
?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 minimum wage thresholds). The expected base rate for this role is between
$100,000 - $160,000
EOE?- Race/Color/Religion/Sex/Sexual?Orientation/Gender Identity/National Origin/ Age/Genetic Information /Protected Veteran/Disability Status
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US Foods is one of America's great food companies and a leading foodservice distributor, partnering with approximately 300,000 restaurants and foodservice operators to help their businesses succeed. With 28,000 employees and more than 70 locations, US Foods provides its customers with a broad and innovative food offering and a comprehensive suite of e-commerce, technology and business solutions. US Foods is headquartered in Rosemont, Ill., and generates more than $28 billion in annual revenue. Visit www.usfoods.com to learn more.
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US Foods, Inc. is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other basis prohibited by applicable law.
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