Sr Analyst, Data Science Enablement

Posted Yesterday
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Folsom, CA, USA
In-Office
Senior level
eCommerce • Fashion
The Role
Drives adoption and value realization of AI/ML models across Gap Inc. brands. Manages stakeholder relationships, creates model explainability materials, coordinates A/B tests, builds adoption dashboards, measures business impact, diagnoses adoption barriers, and integrates model recommendations into merchandising, planning, sourcing, and costing workflows. The role also delivers executive communications, trains business users, and partners with data science and engineering teams on workflow enablement and continuous improvement.
Summary Generated by Built 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 Do

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, Inventory Planning, Sourcing, Design, and Costing — 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

Who You Are
  • 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 client-facing analytics
  • Experience managing multiple senior stakeholder relationships with strong responsiveness and follow-through
  • Exceptional written and verbal communication skills, including executive presentations
  • Ability to structure ambiguous business problems and develop concrete recommendations
  • Data literacy, including model accuracy, confidence intervals, feature importance, A/B testing, and business KPIs
  • Proficiency in SQL and/or Python for data extraction and light analytics
  • Experience with Tableau, Looker, Power BI, or equivalent dashboard tools
  • Experience designing and running structured experiments or pilots and interpreting results
  • Familiarity with retail processes such as merchandising, inventory planning, allocation, or sourcing
  • Familiarity with MLOps concepts, 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)..

  • 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.
  • 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.
  • 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

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The Company
HQ: San Francisco, CA
11,000 Employees
Year Founded: 1969

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.

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