Sr Analyst, Data Science Enablement

About Gap Inc.At Gap Inc., we create culture as much as we create clothes. Our ambition is to become a high-performing house of iconic American brands that shape culture.Our portfolio—Old Navy, Gap, Banana Republic, and Athleta—each brings a distinct point of view to how we show up in the world and serve our customers.Old Navy democratizes style with quality and value for all. Gap champions originality through essential pieces that celebrate individuality. Banana Republic is rooted in a spirit of discovery, creating modern pieces inspired by craftsmanship and travel. Athleta champions the Power of She through confidence, strength, and movement.We’re driven by a shared purpose: to bridge gaps—between people, perspectives, and possibilities—to create a better world.We’re building a team that performs at a high level—people who think boldly, take ownership, and turn ideas into impact. If you’re ready to learn fast and help shape what’s next, you’ll fit right in.About the roleIn this role, you are the bridge between Data Science and the business — responsible for driving adoption of AI and ML models across Gap Inc. brands. You will operate as an internal consultant embedded within the Data Science organization: building trusted relationships with business stakeholders, translating complex model outputs into clear commercial narratives, and ensuring that every model the DS team builds actually drives measurable business impact. Success in this role looks less like coding and more like consulting — structured thinking, reliable delivery, and the ability to make technical complexity feel simple and actionable to merchant, planning, and sourcing leaders.What you'll doModel Adoption & Value RealizationOwn the end-to-end adoption lifecycle for a portfolio of DS models — from first stakeholder introduction through sustained, broad-based useOwn and maintain a library of Model Explainability Cards — one-page business-language explainers for every production AI/ML model in the DS portfolioDesign and coordinate adoption-focused A/B tests embedded in production business workflows, translating experiment results into business-language impact summariesBuild and maintain adoption dashboards that track model coverage, influence rate, override rate, and time-to-adoption by function and brandProduce quarterly per-model business impact reports that quantify margin lift, forecast accuracy improvement, cycle-time reduction, and sell-through impactDiagnose adoption stalls by analyzing override analytics — identifying where and why humans deviate from model recommendations and routing structured findings back to model ownersStakeholder Management & Internal ConsultingBuild and maintain trusted relationships with business partners across Merchandising, Inventory Planning, Sourcing, Design, and Costing — acting as their primary point of contact for all things related to DS model adoptionConduct structured discovery with business teams to diagnose adoption barriers, surface unmet needs, and develop tailored enablement plans by function and brandDevelop and deliver executive-ready presentations, model explainability briefs, and quarterly business impact reports for senior stakeholders up to VP and SVP levelFacilitate workshops, working sessions, and office hours that bring data science outputs to life for non-technical audiencesProactively manage a portfolio of business relationships — tracking open issues, commitments, and follow-through with a high standard of reliability and responsivenessServe as the voice of the business back into the DS team, synthesizing stakeholder feedback and routing prioritized signal to model owners and engineersWorkflow Integration & Change ManagementPartner 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 behaviorTrain and coach business stakeholders on AI model interpretation, appropriate use, and feedback mechanisms; build repeatable onboarding materials that scale across brandsContribute to the institutional DS Enablement playbook, documenting what works, what doesn't, and how to accelerate adoption for future model launchesWho you are3–6 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 preferredDemonstrated ability to manage multiple senior stakeholder relationships simultaneously with a high standard of responsiveness, follow-through, and structured communicationExceptional 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 jargonComfort 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 directionSufficient 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 themProficiency 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 developmentExperience designing and running structured experiments or pilots, with the ability to interpret results and translate statistical findings into plain-language business impactFamiliarity with retail business processes — particularly Merchandising, Inventory Planning, Allocation, or Sourcing — is a meaningful advantage; multi-brand or omnichannel experience is a plusHigh-agency work style: proactively identifies blockers, manages up clearly, and brings a proposed solution alongside every problemFamiliarity 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 advantageSalary Range: $117,700.00 - $153,000.00Employee pay will vary based on factors such as qualifications, experience, skill level, competencies and work location. We will meet minimum wage or minimum of the pay range (whichever is higher) based on city, county and state requirements.Benefits at Gap Inc.Merchandise discount for our brands: 50% off regular-priced merchandise at Old Navy, Gap, Banana Republic and Athleta, and 30% off at Outlet for all employees.One of the most competitive Paid Time Off plans in the industry.*Employees can take up to five “on the clock” hours each month to volunteer at a charity of their choice.*Extensive 401(k) plan with company matching for contributions up to four percent of an employee’s base pay.*Employee stock purchase plan.*Medical, dental, vision and life insurance.*See more of the benefits we offer.*For eligible employees