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
Requirements
3–6 years of experience in management consulting, customer success, or a client-facing analytics role; experience in a high-accountability, client-facing or internal consulting function is strongly preferred
Demonstrated ability to manage multiple senior stakeholder relationships simultaneously with a high standard of responsiveness, follow-through, and structured communication
Exceptional written and verbal communication skills — able to write crisp executive briefs, structure a compelling slide, and present confidently to VP-level audiences without relying on jargon
Comfort operating in ambiguity: able to take an open-ended business problem, frame it clearly, and drive it to a concrete recommendation or deliverable without constant direction
Sufficient data literacy to work credibly alongside a Data Science team — comfortable with concepts such as model accuracy, confidence intervals, feature importance, A/B testing, and business KPIs; does not need to build models but must be able to interrogate and interpret them
Proficiency in SQL and/or Python for pulling data, building adoption metrics, and supporting light analytics; experience with Tableau, Looker, Power BI, or equivalent for dashboard development
Experience designing and running structured experiments or pilots, with the ability to interpret results and translate statistical findings into plain-language business impact
Familiarity with retail business processes — particularly Merchandising, Inventory Planning, Allocation, or Sourcing — is a meaningful advantage; multi-brand or omnichannel experience is a plus
High-agency work style: proactively identifies blockers, manages up clearly, and brings a proposed solution alongside every problem
Familiarity with MLOps concepts (model cards, drift monitoring, override analytics) is a plus; experience partnering with Data Science or Engineering teams in a previous role is an advantage
Skills Required
- 3-6 years of experience in management consulting, customer success, or a client-facing analytics role
- Experience managing multiple senior stakeholder relationships simultaneously
- Exceptional written and verbal communication skills, including executive briefs and presentations
- Ability to operate independently in ambiguity and drive open-ended problems to concrete recommendations or deliverables
- Data literacy covering model accuracy, confidence intervals, feature importance, A/B testing, and business KPIs
- Proficiency in SQL and/or Python
- Experience with Tableau, Looker, Power BI, or equivalent dashboard tools
- Experience designing and running structured experiments or pilots and interpreting statistical results
- High-agency work style with proactive blocker identification and solution-oriented communication
- Experience in a high-accountability, client-facing, or internal consulting function
- Familiarity with retail processes such as merchandising, inventory planning, allocation, or sourcing
- Multi-brand or omnichannel experience
- Familiarity with MLOps concepts, including model cards, drift monitoring, and override analytics
- Experience partnering with Data Science or Engineering teams
Gap (gapinc.com). Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Gap (gapinc.com). and has not been reviewed or approved by Gap (gapinc.com)..
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Healthcare Strength — Comprehensive medical, dental, and vision coverage is offered, alongside programs that support physical, mental, and financial wellbeing. Feedback suggests eligible employees can also leverage tools like FSAs and additional wellbeing resources.
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Leave & Time Off Breadth — Paid time off, company-paid holidays, and multiple leave options (sick, disability, and family leave) create broad time-away coverage. Some roles start with substantial PTO accrual and can access flexible leave arrangements.
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Wellbeing & Lifestyle Benefits — A generous cross-brand merchandise discount is a standout perk, complemented by commuter benefits, on-the-clock volunteer hours, and matching donations. Feedback suggests these lifestyle benefits add meaningful value beyond base pay.
Gap (gapinc.com). Insights
What We Do
In 1969, Don and Doris Fisher opened the first Gap store on Ocean Avenue in San Francisco. They wanted to make it easier to find a great pair of jeans, and they did. Their denim and records store was a hit, and it grew to become one of the world’s most iconic brands. Today we’re represented in more than 1400 stores in over 40 countries, and online. We have headquarters in New York, London, Shanghai, Tokyo, and, of course, San Francisco. Our unique aesthetic is optimistic cool, elevated American style. Our clothes are crafted with care, with focused attention to thoughtful design. We believe in staying true to our heritage while creating what’s next. Don and Doris Fisher always wanted to “do more than sell clothes.” They wanted to support the people who ran their company, to be active in their communities, and to have a positive impact on the world. Their vision helped transform retail, and we’re still following their lead. We stand for freedom and possibility for all; we champion diverse ideas that transcend generations, geographies and genders.
