Data Scientist II - Customer Analytics

Gap, Inc.

$120K — $145K *
Retail & Consumer Goods
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's or master's degree in a quantitative field with relevant experience (5+ years or 3+ years, respectively).
  • Proven experience leading complex analytical projects from inception to actionable recommendations.
  • Advanced SQL skills with familiarity in handling large datasets in cloud environments.
  • Proficiency in Python, R, Spark, or similar analytical tools.
  • Strong communication skills for presenting findings to senior stakeholders.
  • Self-motivated and capable of juggling multiple priorities while driving work independently.

Responsibilities

  • Lead end-to-end analytical projects, delivering actionable insights from complex business questions.
  • Analyze large datasets to uncover growth opportunities and factors influencing business performance.
  • Translate analytical findings into concise, executive-ready narratives for stakeholders.
  • Develop customer and product analytics to shape business strategies based on behavioral insights.
  • Integrate diverse data sources to form a comprehensive understanding of customer and market dynamics.
  • Apply advanced statistical and machine learning techniques to enhance decision-making.
  • Build relationships with business leaders to align analytical projects with strategic priorities.

Benefits

  • Collaborative and inclusive work culture.
  • Opportunity to drive measurable business impact through data insights.
  • Access to diverse datasets and innovative analytical tools.
  • Professional development opportunities in a leading retail context.
  • Flexible work arrangements to support work-life balance.
Full Job Description
About the Role
The Data Science team at Gap Inc. transforms customer, product, digital, and market data into insights that drive measurable business impact. The successful candidate will lead high-impact analyses across customer acquisition and retention, product and basket performance, digital engagement, and omnichannel behavior.

This role requires analytical rigor, business acumen, data storytelling, and strong stakeholder management. The ideal candidate can structure ambiguous business questions, connect insights across internal and external data sources, and clearly articulate what is happening, why it matters, and what actions to take.What You'll Do
  • The ideal candidate is an applied, business-facing data scientist who pairs strong technical capabilities with a passion for working directly with business partners, using analytics and modeling to drive decisions rather than focusing primarily on behind-the-scenes model development.
  • Lead end-to-end analytical projects, from framing complex business questions and developing the analytical approach to delivering actionable recommendations and measuring impact.
  • Analyze large customer, transaction, product, marketing, and digital datasets to identify growth opportunities and business performance drivers.
  • Translate complex findings into concise, executive-ready narratives that clearly communicate the "so what," recommended actions, trade-offs, and expected impact.
  • Develop customer and product analytics-including lifecycle, segmentation, basket, cross-shopping, cohort, funnel, and behavioral analyses-to inform business strategy.
  • Integrate internal data with external sources, such as consumer trends, search behavior, competitive intelligence, and market research, to build a holistic view of the customer and business.
  • Apply statistical, predictive, causal, and machine learning techniques when appropriate to improve business decision-making.
  • Develop scalable analytical frameworks, reusable datasets, and automated processes that enable consistent measurement and reduce manual work.
  • Partner with business leaders, product managers, data scientists, engineers, and technology teams to translate business priorities into analytical roadmaps and deliverables.
  • Build trusted stakeholder relationships, proactively identify emerging needs, constructively challenge assumptions, and influence decisions through clear, data-backed recommendations.
Who You Are

Required Qualifications
  • Bachelor's degree with 5+ years of relevant experience, or master's degree with 3+ years of relevant experience, in Data Science, Statistics, Economics, Computer Science, Applied Mathematics, or another quantitative field.
  • Proven ability to lead complex analytical projects from problem definition through recommendation and business activation.
  • Advanced proficiency in SQL and experience working with large datasets in distributed or cloud environments.
  • Proficiency in Python, R, Spark, or other modern analytics and data science tools.
  • Strong written and verbal communication skills, including experience presenting recommendations to senior stakeholders.
  • Self-starter with the ability to work independently, proactively drive work forward, manage multiple priorities, and collaborate effectively across functions.


Preferred Qualifications
  • Experience in DTC retail, apparel, e-commerce, consumer products, or another customer-focused industry.
  • Experience analyzing customer lifecycle, acquisition, retention, loyalty, product performance, or omnichannel behavior.
  • Experience with basket analysis, product affinity, cross-shopping, or customer-product relationships.
  • Experience integrating external data-such as search trends, consumer research, competitive intelligence, social listening, or market data-with internal performance data.
  • Experience with digital analytics, including website or app engagement, customer journeys, conversion funnels, and marketing channel performance.

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