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.
+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