About Yext
Yext (NYSE: YEXT) is the enterprise agentic marketing platform. Built on the world's most comprehensive structured data platform for local businesses, Yext gives brands and their partners the visibility intelligence to win every moment of discovery – across AI and traditional search. Yext's API-first architecture connects structured data to APIs, MCP servers, and generative interfaces, so partners and developers can build purpose-built experiences on the same infrastructure powering Yext's own products. Thousands of brands and digital marketing partners in financial services, healthcare, retail, hospitality, and food rely on Yext to manage, measure, and optimize visibility at scale.
In 2024, Yext acquired Hearsay Systems, bringing together two industry leaders to form one unified organization. By combining Yext's brand visibility expertise with Hearsay's best-in-class compliant engagement solutions, Yext is delivering even greater value to its customers. The integrated approach unlocks a deeper set of data, insights, and recommendations — empowering brands to convert prospects into customers faster and more effectively.
As an AI-first organization using modern AI and agentic workflows, Yext is seeking a Data Scientist to transform data assets into measurable business value and product capabilities by designing reliable data products, methodologies, and cross-functional features from concept to production.
Responsibilities
•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.
Requirements
•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.
