Model Adoption & Value Realization 

• Own the end-to-end adoption lifecycle for a portfolio of DS models — from first stakeholder introduction through sustained, broad-based use 

• Own and maintain a library of Model Explainability Cards — one-page business-language explainers for every production AI/ML model in the DS portfolio 

• Design and coordinate adoption-focused A/B tests embedded in production business workflows, translating experiment results into business-language impact summaries 

• Build and maintain adoption dashboards that track model coverage, influence rate, override rate, and time-to-adoption by function and brand 

• Produce quarterly per-model business impact reports that quantify margin lift, forecast accuracy improvement, cycle-time reduction, and sell-through impact 

• Diagnose adoption stalls by analyzing override analytics — identifying where and why humans deviate from model recommendations and routing structured findings back to model owners 

Stakeholder Management & Internal Consulting 

• Build and maintain trusted relationships with business partners across Merchandising, Merchandise Planning, and Inventory Management— acting as their primary point of contact for all things related to DS model adoption 

• Conduct structured discovery with business teams to diagnose adoption barriers, surface unmet needs, and develop tailored enablement plans by function and brand 

• Develop and deliver executive-ready presentations, model explainability briefs, and quarterly business impact reports for senior stakeholders up to VP and SVP level 

• Facilitate workshops, working sessions, and office hours that bring data science outputs to life for non-technical audiences 

• Proactively manage a portfolio of business relationships — tracking open issues, commitments, and follow-through with a high standard of reliability and responsiveness 

• Serve as the voice of the business back into the DS team, synthesizing stakeholder feedback and routing prioritized signal to model owners and engineers 

Workflow Integration & Change Management 

• Partner with business users and DS domain leads to redesign human-AI workflows so that model recommendations are embedded naturally in existing tools — PLM, planning platforms, costing tools, and sourcing systems — rather than requiring users to change behavior 

• Train and coach business stakeholders on AI model interpretation, appropriate use, and feedback mechanisms; build repeatable onboarding materials that scale across brands 

• Contribute to the institutional DS Enablement playbook, documenting what works, what doesn't, and how to accelerate adoption for future model launches