Data Scientist II - Customer Analytics

Gap Inc.; San Francisco (CA); On-site; USD 140,000 - 210,000; Full time

Job summary

Gap Inc.’s Data Science team leads analyses across customer acquisition, product performance, and omnichannel behavior, turning data into measurable business impact. The role requires analytical rigor, business acumen, data storytelling, and strong stakeholder management.

You will structure ambiguous questions, connect data sources, and translate insights into actionable recommendations. Expect collaboration with product, engineering, and marketing to drive growth and improve decision-making

Qualifications

• 5+ years of experience in data science or analytics.
• Experience leading complex analytical projects end-to-end.
• Strong SQL skills with large datasets.
• Proficiency in Python or R and Spark.
• Excellent written and verbal communication.
• Ability to interact with senior stakeholders.

Responsibilities

• Lead end-to-end analytical projects from framing complex business questions to delivering actionable recommendations.
• Analyze large customer, transaction, product, and engagement datasets to identify growth opportunities and drivers.
• Translate complex findings into concise, executive-ready narratives that communicate impact and actions.
• Develop customer and product analytics including segmentation, funnel, and cohort analyses.
• Integrate internal data with external sources to build a holistic view of customer and business.
• Apply statistical, predictive, causal, and ML techniques to improve decision-making.
• Develop scalable analytical frameworks, reusable datasets, and automated processes.

Skills

SQL

Python

R

Spark

Big data

Communication

Independent work

Stakeholder management

Data storytelling

Education

Bachelor’s degree in a quantitative field

Tools

Spark

Cloud platforms

Job description

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 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

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