Principal Data Product Manager, Toast

• Relevant Experience: 6+ years of experience in analytics, data science, ML, or NLP in a data-intensive environment
• AI Fluency: Practical fluency with LLMs, including prompt engineering, structured output extraction, and model evaluation
• Product Instincts: You think about what you are building in terms of who uses it and how you will know if it is working
• Project Leadership: Strong program and stakeholder management skills with the ability to move things forward without formal authority
• Technical Expertise: Applied experience with text data and NLP/ML techniques such as LLMs, classifiers, or embeddings
• Core Skills: Expert-level SQL and solid Python proficiency with the ability to build and iterate on ML pipelines independently
• Communication Mastery: Ability to explain complex classification pipelines to non-technical leaders and push back on requirements when necessary

Desirable

• The Customer Success Data and Analytics (CSDA) team supports Care Operations, Customer Success, Education, and Voice of the Customer. We are building a new generation of data products that extract structured, actionable insight from unstructured customer interactions using NLP, ML, and LLM-based approaches
• As the Principal Data Product Manager, Applied AI, you will own the agenda for how AI-enriched data improves our understanding of the customer experience. You will prototype, validate, and scale a portfolio of AI-powered data products that give our CS organization insight it has never had before
• You will also serve as a resource and thought partner for teammates and other teams across Toast who are working with CS data in an AI context, helping make that work faster, more consistent, and more reliable
• This is a hands-on, high-ownership role. You will spend time in Snowflake and Hex building things, and you will spend time with CS leaders explaining what those things mean and why they matter. The right person for this role is equally comfortable doing both
• Technical Resource: Serve as the go-to resource on applied AI and NLP with CS data for your CSDA teammates and other teams across Toast
• Best Practices: Build and maintain a practical library of guidance regarding successful prompts, pitfalls to watch for, and how to structure CS data for AI use cases
• Market Intelligence: Stay current on how CS data is being used with AI tools across the organization to keep CSDA ahead of the curve
• Facilitation: Act as a facilitator for AI prototyping work, helping analysts and stakeholders structure experiments so outputs are reliable and usable
• Portfolio Ownership: Drive an active portfolio of prototyping work focused on enriching the CSDA data model with insight extracted from unstructured contact data
• Strategic Focus: Focus on contact classification, intelligent summarization, sentiment analysis, churn signal detection, and product mention extraction
• End-to-End Design: Manage the pipeline from problem framing and prompt design to embedding generation, classifier training, and final production
• Stakeholder Validation: Run structured validation processes, including codebook reviews and labeling sessions, to earn trust before products scale
• Readiness Framework: Maintain a clear framework for deciding what is ready to scale based on business value, quality, and maintenance requirements
• Engineering Partnership: Partner closely with the CSDA data engineering team to scope and hand off production-grade implementations
• Quality Governance: Own the quality review process for AI products in production, including monitoring for output drift and driving recalibration
• Product Advocacy: Serve as the face of these products with stakeholders, explaining how they work and being honest about their limitations