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# Data Scientist

- **Company:** Yext, Inc.
- **Location:** New York, United States (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Microsoft Azure, Data Warehousing, Python (Programming Language), Machine Learning, Software Deployment, SQL Databases, Unstructured Data, Cloud Platform System, Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, Model Validation, AI Coding Agents, Agentic-AI, Information Technology, Data Analytics, Claude, Data Pipelines, Unsupervised Learning
- **Published:** November 7, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/px8iw7l19a

## About the Role

* 3+ years of experience in data science, machine learning, or data analytics.
 * Proficiency in Python and SQL for data analysis, modeling, and experimentation.
 * Solid understanding of statistics, supervised/unsupervised learning, and model validation techniques.
 * Experience with data modeling, data warehousing, and preparing datasets for analytical and product use.
 * Familiarity with generative AI/LLM applications (e.g., RAG, prompt engineering, agentic workflows, evaluation).
 * AI-first mindset utilizing AI coding assistants (e.g., Codex, Claude) while ensuring quality and security.
 * Hands-on experience in cloud environments (AWS, GCP, or Azure).
 * Strong problem-solving ability and comfort working independently through ambiguity.
 * Excellent communication and cross-functional collaboration skills.
 * Bachelor's or Master's in Computer Science, Engineering, Math, or equivalent practical experience.

## Description

* Identify product and business opportunities by analyzing the structure, quality, and capabilities of Yext's data sources.
 * Design data models and metrics to power innovative customer-facing features and decision-making.
 * Lead high-impact data science and ML research from problem framing through prototyping to engineering handoff.
 * Leverage AI-first tools and agentic workflows (e.g., Codex, Claude, Coco) for efficient research, coding, and testing.
 * Develop and evaluate statistical, ML, and GenAI/LLM solutions across structured and unstructured data.
 * Build reproducible prototypes and validate model quality, coverage, and business impact prior to production deployment.
 * Partner with Product, Engineering, and business stakeholders to turn ambiguous opportunities into production solutions.
 * Collaborate with Engineering to enhance data pipelines, data quality, and overall data stack architecture.
 * Clearly communicate findings, trade-offs, and promote evidence-based, responsible AI adoption.
 * Mentor teammates and continuously explore emerging AI methods to boost team capabilities.