About the Role

What You'll Do

Advanced Analytics and Modeling: 

• 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 cutting-edge machine learning algorithms, including but not limited to deep learning, ensemble methods, and natural language processing, to analyze large-scale datasets related to customer behavior, product attributes, and digital commerce performance. 

• Utilize advanced analytics, machine learning, and statistical modeling techniques to analyze large volumes of structured and unstructured data related to customer behavior, product trends, and digital commerce performance. 

Leadership and Strategy: 

• Provide strategic direction and thought leadership in the application of data science techniques to drive enterprise growth and enhance customer experiences. 

• Collaborate with senior leadership to define and prioritize data science initiatives aligned with business objectives and digital commerce strategies. 

• Mentor & develop data scientists, fostering a culture of innovation, collaboration, and continuous learning. 

Experimentation and Optimization: 

• Design and execute A/B tests and multivariate experiments to evaluate the impact of data-driven initiatives, inform product development decisions, and drive continuous optimization of enterprise processes & outcomes. 

• Develop experimentation frameworks, statistical methodologies, and tooling to facilitate rigorous hypothesis testing and interpretation of experimental results. 

Cross-Functional Collaboration: 

• Partner closely with product management, Gap Inc brands, and technology teams to understand business requirements, identify opportunities for data-driven optimizations, and influence product roadmap decisions. 

• Communicate complex analytical findings and insights effectively to stakeholders at all levels, fostering data-driven decision-making across the organization. 

• Collaborate with data engineering and IT teams to ensure data accessibility, integrity, and scalability for analytics and modeling purposes. 

Innovation and Continuous Improvement: 

• Stay abreast of emerging trends, technologies, and best practices in data science, retail industries, and operations research. 

• Identify opportunities for innovation and experimentation, leading the exploration and implementation of new analytical techniques, tools, and methodologies. 

• Drive process improvements and establish best practices for data science workflows, model deployment, and performance monitoring. 

Who You Are

• Advanced experience in data science, machine learning, or analytics roles, preferably within the retail or e-commerce industry. 

• Proven track record of leading data science initiatives, driving business impact, and delivering actionable insights in a fast-paced environment. 

• Expertise in statistical modeling, machine learning algorithms, and data mining techniques, with proficiency in programming languages such as Python, R, or SQL. 

• Strong communication and stakeholder management skills, with the ability to distill complex technical concepts into clear and actionable insights for non-technical audiences. 

• Experience leading and mentoring cross-functional teams of data scientists, analysts, or engineers. 

• Familiarity with digital commerce platforms, customer relationship management (CRM) systems, and web analytics tools is a plus. 

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