Sr. Data Scientist - Customer Analytics

About the Role

The Customer Analytics Team at Gap Inc. applies data analysis and statistical modeling techniques to drive business benefits for Gap Inc. and its brands. The team’s focus is on creating analytical capabilities to support customer acquisition and retention, personalization and marketing at Gap Inc. Areas of expertise include digital analytics, customer behaviors, forecasting, incrementality and causal inference. You will support the team to build and deploy Data and Analytics capabilities and actionable insights, in partnership with GapTech, PDM, Central Marketing & business partners across our brands.

What You'll Do

• Synthesize and story tell data to deliver actionable insights across functions. Present compelling data stories (verbal and slide format) to varying levels of stakeholders, including executive leadership.

• Build cross functional partnerships and consensus, and influence strategy of domain areas.

• Manipulate large amounts of data across a diverse set of subject areas (digital, customer, inventory, marketing, etc.) and develop statistical models and analysis to uncover actionable insights and trends.

• Collaborate with other data scientists and data engineers to prepare and automate data pipelines from multiple disparate sources for analysis and modeling.

• Develop compelling visualizations that support actionable insights and produce decks and presentations that are executive-ready.

• Build repeatable solutions that can identify trends and insights on a regular cadence.

• Mentor more junior team members and grow the technical and data storytelling skillsets of the team.

Who You Are

• Have strong business acumen and understanding of retail business drivers.

• Ability to work both at a detailed level as well as to summarize findings and extrapolate knowledge to make strong recommendations for change. Have strong verbal and written communication skills, and able to present to senior executives.

• Ability to collaborate with cross functional teams and influence product and analytics roadmap, with a demonstrated proficiency in relationship building.

• Have experience using Adobe Analytics suite to uncovering digital experience trends and insights.

• Have advanced proficiency using SQL for efficient manipulation of large datasets in on-prem and cloud-distributed computing environments, such as Azure environments

• Have proficiency in Python, Spark, and common scripting languages for E2E pipeline.

• Have experience using causal inference methods to measure incrementality and estimate causal effects.

• Have experience with supervised and unsupervised learning ML techniques, visualization packages, and a track record for creating business impact with these methods.

• Ability to work in ambiguous and complex situations and analyze data to make judgments and recommend solutions.

• A track record of being a self-starter who can execute and drive roadmaps.