About the Role

This role sits in our beautiful San Francisco hub office.

As a Senior Data Scientist for the Customer Data Science team at Gap Inc, you will be part of is a highly visible team bringing direct impact to senior leaders across our four iconic brands: Old Navy, Gap, Banana Republic and Athleta. You will play a pivotal role in leveraging advanced analytics and machine learning to drive growth, optimize customer experience and enhance operational excellence across Gap Inc brands. This team is chartered with spearheading data-driven initiatives that address the most important and timely opportunities to the Business, empowering leadership to make informed decisions in areas having the highest impact on financial performance and long-term customer equity.

Reporting to the Customer Data Science Director, you will focus on delivering a portfolio of predictive models and inferential decision assets while driving a customer-first mindset across business units. You will leverage your expertise in Causal Inference and Econometrics to socialize robust practices in causal impact assessment, KPI forecasting and elasticities, across a large and like-minded data scientist peer group as well as brand embedded business analysts. As a senior member of the team, your efforts will further mature internal data products designed to measure value across channels and customer dimensions, optimize promotional cadence, and shape marketing decisions across a full suite of paid, owned and earned marketing.

What You'll Do

Modeled Insights and Inference  

• Create a comprehensive Causal ML framework to measure impact. 

• Develop approaches to measure cross-price elasticity, SKU demand transference, cannibalization, and other causal treatment outcomes. 

• Apply modern machine learning algorithms, including deep learning, ensemble methods, and LLMs, to analyze large-scale datasets containing customer interactions with product and platform attributes.

• Guide audience targeting strategy across CRM, digital, App through customer lifecycle propensity modeling to acquire and retain.  

 

Leadership and Strategy 

• Influence design and execution of multivariate experiments, KPI rationalization, establish measurement protocols with and without controlled setup, arbitrate over statistical and business significance.  

• Communicate complex analytic findings and insights effectively to stakeholders at all levels. 

• Partner closely with product management, Gap Brand ecommerce and marketing leads to understand business hypotheses, requirements, and opportunities to influence decisions, roadmaps. 

• Partner with Data Engineering, Data Governance, Platform and Transformation teams to ensure data consistency, accessibility and scalability and useability for analytic intent. 

 

Team and Culture  

• Stay abreast of emerging trends, best practices, and tools for acquiring external intelligence, leading the exploration and implementation of new analytics data sources or techniques.  

• Use audience appropriate visualizations to drive strategic adoption, tell a story, diagnose performance and identify opportunities. 

Who You Are

• MS/PhD in mathematics, statistics, data science, econometrics, operations research or similar. 

• Expert level experience as a data scientist in predictive solution development and revenue impact measurement.   

• Established experience working with customer level behavioral data, preferably with a multi-channel retailer. 

• Advanced proficiency using SQL for efficient manipulation of large datasets, Azure Databricks. 

• Demonstrated ability to research, evaluate and apply appropriate methodologies over a broad array of business interests, overseeing causal inference; Causal Impact, synthetic control, diff-of-diff. 

• Python experience directed towards statistical modeling, machine learning algorithms (regression and boosting trees, SVM and similarity methods, time series) and a track record for creating business impact with these methods, preferably in service of acquisition and retention goals.  

• Critical thinking, agile mindset, strong written and verbal communication skills exercised across all levels of business hierarchy, with a demonstrated appetite for relationship building.  

• Passion for retail, fashion, and consumer behavior, with a deep understanding of the digital commerce ecosystem, and industry trends