Principal Data Scientist – Generative Recommendations, Agentic Orchestration

• Drive the generative, intent-based, and agentic evolution of Vista's Customer Relevance Platform
• Act as the primary technical bridge between core ML/data science modeling and modern LLM application layers
• Translate classical recommendations, graph embeddings, and fmX outputs into reasoning abstractions for agentic workflows
• Co-lead the research agenda with another Principal Data Scientist
• Design and build the agentic reasoning layer around fmX models and rankers
• Implement self-correction, reasoning, and contextual explanation patterns for recommendations
• Architect and build ML pathways and Model Context Protocol (MCP) servers exposing recommendation models and data as modular tools for AI agents
• Enable conversational shopping experiences to query, rank, and synthesize candidates in real time
• Develop an algorithmic intent layer using real-time browsing and session signals
• Build propensity models and use behavioral traits for actionable customer segmentations and dynamic personas
• Serve as Vista's AI ambassador across product, engineering, and business leadership
• Ensure models integrate with delivery systems without negatively affecting Core Web Vitals or caching efficiency

• Advanced degree (Ph.D. or Master's) in Computer Science, Applied Mathematics, Statistics, or a closely related quantitative field
• 8+ years of experience building and deploying machine learning models and deep learning systems into high-scale customer experiences
• Hands-on experience and proactive experimentation with Agentic AI and AI Agent Orchestration frameworks such as LangGraph and Strands
• Experience building reasoning layers, including advanced chain-of-thought, self-correction, or validation loops
• Demonstrated experience or active experimentation building Model Context Protocol (MCP) servers to bridge data/ML systems with LLM orchestrators in a production context
• Deep expertise in Deep Learning, Large Language Models (LLMs), and Reinforcement Learning, especially for real-time feedback loops or personalized ranking
• Proven track record building propensity models and customer segmentation models on large-scale behavioral data
• Expert-level proficiency in Python, PyTorch/TensorFlow, and SQL
• Strong architectural understanding of ML models interacting with backend pipelines such as Databricks, Snowflake, and streaming features, and frontend delivery systems such as UI rendering, caching strategies, and latency management
• Very strong communication and stakeholder management skills
• Ability to translate complex statistical and algorithmic concepts into clear business value and influence non-technical leaders
• Ability to align cross-functional engineering teams

• Remote-First company
• Inclusive community
• Growth opportunities
• Vista Behaviors supporting a culturally strong and high-performing team
• Equal employment opportunity