Principal Data Scientist – Generative Recommendations, Agentic Orchestration

This is a fully remote position, open to applicants in Spain.

📋 Description

• Lead the generative, intent-driven, and agentic advancement of Vista's Customer Relevance Platform.

• Serve as the main technical liaison between core machine learning/data science modeling and contemporary large language model application layers.

• Convert traditional recommendations, graph embeddings, and fmX outputs into reasoning abstractions suitable for agentic workflows.

• Co-manage the research agenda alongside another Principal Data Scientist.

• Design and construct the agentic reasoning layer surrounding fmX models and ranking algorithms.

• Implement self-correction, reasoning, and contextual explanation strategies for recommendations.

• Architect and develop ML pathways and Model Context Protocol (MCP) servers that expose recommendation models and data as modular tools for AI agents.

• Facilitate conversational shopping experiences that query, rank, and synthesize candidates in real-time.

• Create an algorithmic intent layer utilizing real-time browsing and session signals.

• Develop propensity models and leverage behavioral traits for actionable customer segmentations and dynamic personas.

• Act as Vista's AI ambassador across product, engineering, and business leadership teams.

• Ensure model integration with delivery systems without adversely impacting Core Web Vitals or caching efficiency.

⛳️ Requirements

• An advanced degree (Ph.D. or Master's) in Computer Science, Applied Mathematics, Statistics, or a closely related quantitative discipline.

• Over 8 years of experience in building and deploying machine learning models and deep learning systems within high-scale customer experiences.

• Practical experience and proactive experimentation with Agentic AI and AI Agent Orchestration frameworks such as LangGraph and Strands.

• Proven experience in developing reasoning layers, including advanced chain-of-thought, self-correction, or validation loops.

• Demonstrated experience or active experimentation in constructing Model Context Protocol (MCP) servers to connect data/ML systems with LLM orchestrators in a production environment.

• In-depth expertise in Deep Learning, Large Language Models (LLMs), and Reinforcement Learning, particularly regarding real-time feedback loops or personalized ranking.

• A solid track record of building propensity models and customer segmentation models on extensive behavioral datasets.

• Expert-level proficiency in Python, PyTorch/TensorFlow, and SQL.

• Strong architectural knowledge of ML models interacting with backend pipelines like Databricks, Snowflake, and streaming features, as well as frontend delivery systems such as UI rendering, caching strategies, and latency management.

• Exceptional communication and stakeholder management abilities.

• Capable of translating complex statistical and algorithmic concepts into clear business value and influencing non-technical stakeholders.

• Ability to align cross-functional engineering teams effectively.

🏝️ Benefits

• Remote-First company.

• Inclusive community.

• Growth opportunities.

• Vista Behaviors that promote a culturally strong and high-performing team.

• Equal employment opportunity.