[Hiring] Principal Data Scientist @Cimpress/Vista

Role Description

As the Principal Data Scientist, you will drive the generative, intent-based, and agentic evolution of our platform. A critical part of your role will be to act as the primary bridge between traditional data science practices (ranking, embeddings, deep learning) and advanced LLM / Agentic reasoning layers. You will partner directly with another Principal Data Scientist to co-lead our research agenda, accelerating our strategic progress and elevating the capabilities of the wider Data Science team.

• Bridging Data Science & Agentic Experiences: Act as the primary technical bridge between core ML/DS modeling and modern LLM application layers. Translate classical recommendations, graph embeddings, and fmX outputs into robust reasoning abstractions for use in agentic workflows.
• Agentic Reasoning & Recommendations: Lead the evolution of recommendations into the Generative AI era. Design and build the agentic reasoning layer that wraps around our fmX models and rankers. Implement patterns that allow models to self-correct, reason, and contextually explain recommendations to customers.
• Tool-Use & MCP Architecture: Architect and build the ML pathways and Model Context Protocol (MCP) servers to expose core recommendation models and data as modular tools for AI agents. This allows conversational shopping experiences to dynamically query, rank, and synthesize candidates in real time.
• Intent-Based Personalization: Develop an algorithmic intent layer that translates real-time browsing and session signals into structured, context-aware customer intents to feed directly into the fmX-based recommendation pipeline.
• Broad Personalization & Segmentation: Build advanced propensity models and leverage behavioral traits to drive actionable, business-aligned customer segmentations and dynamic personas.
• AI Leadership & Strategy: Act as Vista's AI ambassador, influencing product, engineering, and business leadership to adopt a model-driven, agent-first approach. Ensure models integrate cleanly with delivery systems without hurting Core Web Vitals or caching efficiency.

Qualifications

• 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, AI Agent Orchestration frameworks (e.g., LangGraph, Strands, etc.), and building reasoning layers (such as advanced chain-of-thought, self-correction, or validation loops).
• Demonstrated experience or active thinking/experimentation in 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 applied to real-time feedback loops or personalized ranking).
• Proven track record of 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 how ML models interact with both backend pipelines (Databricks, Snowflake, streaming features) and frontend delivery systems (UI rendering, caching strategies, latency management).
• Very strong communication and stakeholder management skills, with a proven ability to translate complex statistical and algorithmic concepts into clear business value to influence non-technical leaders and align cross-functional engineering teams.

Benefits

• Award-winning Remote-First company.
• Inclusive community.
• Opportunities for growth.
• Vista Behaviors that exemplify the behavioral attributes of a culturally strong and high-performing team.