Principal Data Scientist Generative Recommendations & AI

• Drive the generative and context-aware evolution of the platform, partnering with another Principal Data Scientist to co-lead research agenda.
• Lead the evolution of recommendation systems into the Generative AI era, researching generative recommendation paradigms.
• Develop an algorithmic intent layer translating real-time browsing signals into actionable customer intents.
• Architect ML pathways to expose core recommendation actions as tools for AI agents.
• Build advanced propensity models and leverage foundational customer traits to drive customer segmentation and personas.
• Ensure segmentations are actionable and aligned with company strategy.
• Build multi-layered hybrid machine learning models for bot detection, classify ambiguous sessions, and protect analytics and personalization integrity.
• Partner closely with the other Principal Data Scientist to accelerate research initiatives.
• Act as primary AI ambassador influencing product, engineering, and business leadership.
• Work with platform and experience teams to ensure ML models integrate seamlessly without degrading Core Web Vitals or caching efficiency.

Experience: 8+ Years building and deploying machine learning models and LLMs into high-scale customer experiences, * Advanced degree (Ph.D. or Master’s) in Computer Science, Applied Mathematics, Statistics, or a related field.

• 8+ years of experience deploying ML models into high-scale customer experiences.
• Deep expertise in Deep Learning, Large Language Models, and Reinforcement Learning.
• Proven track record building robust propensity models, segmentation frameworks, and anomaly/bot detection algorithms on large-scale behavioral data.
• Expert-level proficiency in Python, PyTorch/TensorFlow, and SQL.
• Strong architectural understanding of ML models with backend data pipelines (streaming features, Databricks, Snowflake) and frontend delivery systems (UI rendering, caching).
• Very strong communication and stakeholder management skills.
• Proven ability to translate complex statistical and algorithmic concepts into clear business value for non-technical leadership.
• Relevant experience in an Agile environment and in e-commerce or marketing domain.