AI Activation, Data Science Manager

USANA Health Sciences

AI Activation & Data Science Manager responsible for data science initiatives at USANA Health Sciences. Leading projects from concept to delivery while coordinating resources and ensuring quality.

Posted 6/5/2026full-timeSalt Lake City • Utah • 🇺🇸 United StatesMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

AzurePythonScikit-LearnSQL

About the role

Key responsibilities & impact

Manage the production process from concept through completion, ensuring creative quality while coordinating timelines, budgets, and resources
Drive active data science projects to production — including a Next Best Action engine, customer segmentation model, and comp plan chatbot — defining what "done" looks like and holding the team accountable to shipping
Establish a delivery cadence that balances exploration with execution, mentoring data scientists toward outcome-oriented habits: scoping work to what can be shipped, documenting what was built, and handing off cleanly
Own the AI activation layer — ensuring data and models reach business users through practical surfaces, including Copilot, Fabric Agents, Power Automate flows, and Emarsys integrations
Configure and optimize Microsoft Fabric semantic models for AI consumption and build MCP server integrations between Fabric and Claude (or equivalent) to make USANA's data accessible within internal AI tools
Set technical direction for applied AI and ML — recommendation systems, customer segmentation, predictive churn, and intelligent automation — ensuring models are understood end-to-end from development through production handoff
Partner with executive and commercial stakeholders to identify high-impact AI opportunities, translating complex technical concepts into actionable business strategies while championing responsible AI practices
Collaborate cross-functionally with BI, marketing, data engineering, and IT teams to deliver end-to-end solutions built on trusted, well-governed data from USANA's Snowflake medallion architecture
Define standards for model lifecycle management, feature engineering, and AI integration patterns — and stay current on the Microsoft AI ecosystem to evaluate emerging tools for strategic adoption

Requirements

What you’ll need

Bachelor's degree in Computer Science , Data Science, Statistics, Mathematics, Engineering, or a related field — or equivalent professional experience; an advanced degree is a plus
5+ years of combined experience in data science, BI, or applied AI roles, with demonstrated depth in machine learning and model deployment and/or data activation — building integrations, automations, or AI surfaces that reach end users
2+ years of experience leading, mentoring, or managing technical team members
Proven experience with the Microsoft AI and data ecosystem: Microsoft Fabric, Power BI semantic models, Copilot, Power Automate, and/or Azure AI services
Experience deploying or activating AI in customer-facing or business-user-facing contexts — Copilot integrations, chatbots in production, automated email triggers, or self-service analytics tools
Proficiency in Python and SQL; familiarity with ML frameworks such as scikit-learn or XGBoost
Genuine enthusiasm for low-code and AI-native tools as accelerants — Power Automate, Fabric Agents, and MCP integrations as real engineering, not workarounds
Strong delivery orientation, excellent cross-functional communication skills, and comfort operating in a fast-moving, ambiguous environment

Benefits

Comp & perks

Health, Dental, Vision, Life and Disability Insurance
On-site medical and mental health clinic for you and your dependents
Flexible paid time off , including sick time, vacation, holidays, family hours, and floating holidays
Paid parental leave for both primary and secondary caregivers
401k match and profit-sharing bonus
Chiropractor visits, massages, fitness classes, and full-service gym
Free and discounted USANA products
Tuition reimbursement, mentorship opportunities, and learning and development licenses

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data sciencemachine learningmodel deploymentfeature engineeringPythonSQLscikit-learnXGBoostAI integrationcustomer segmentation

Soft Skills

mentoringcross-functional communicationdelivery orientationleadershipaccountabilitystrategic thinkingoutcome-oriented habitscollaborationadaptabilityproblem-solving

Certifications

Bachelor's degree in Computer ScienceBachelor's degree in Data ScienceBachelor's degree in StatisticsBachelor's degree in MathematicsBachelor's degree in Engineeringadvanced degree (preferred)