Director of Data Science - Recommendations and E-Commerce
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Job Description
About the Role
As the Director of Data Science for Recommendations and E-Commerce AI at Gap Inc, you will be responsible for providing strategic leadership, vision, and direction to a high-performing team. You will lead the development and optimization of AI Systems that drive personalization for Gap’s digital business, working closely with cross-functional teams to deliver personalized and engaging experiences for our customers.What You'll Do
Strategic Leadership:
Provide strategic direction for the development and evolution of an in-house Recommendation system.
Collaborate with executive leadership to align data science strategies with overall business objectives.
Own the roadmap for AI capabilities to drive Gap Inc.’s digital businesses.
Team Management:
Lead, mentor, and inspire a team of data scientists, ensuring a collaborative and innovative work environment.
Foster a culture of continuous learning, professional development, and knowledge sharing.
Algorithm Development:
Oversee the design, development, and implementation of advanced recommendation algorithms.
Stay abreast of industry trends and emerging technologies in search, recommendation systems, and E-Commerce Personalization.
Cross-Functional Collaboration:
Collaborate with product managers, engineers, and UX designers to integrate data-driven insights into the product development lifecycle.
Work closely with stakeholders to understand business requirements and translate them into actionable data science initiatives.
Experimentation and Optimization:
Drive continuous optimization efforts based on user feedback and performance metrics.
Communication:
Communicate complex technical concepts and insights to non-technical stakeholders, providing regular updates on the performance of search and recommendation systems.
Present findings and recommendations to executive leadership.
Who You Are
Proven experience in leading data science teams with a focus on digital commerce and recommendation systems.
Strong proficiency in Python
Expertise in machine learning techniques, natural language processing, and recommendation algorithms
Excellent leadership and communication skills with the ability to influence strategic decisions.
Experience with deploying production AI systems with real time latency
Proven people and team leadership