Job description

About the Role As a Sr 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, Bana 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 Sr 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 • +8 years of industry-relevant experience as a data scientist in predictive solution development and revenue impact measurement. • +4 years of 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; CausalImpact, 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

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