Staff Data Scientist: Semantic Substrate Incubation

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At Qualtrics, we create software the world's best brands use to deliver exceptional frontline experiences, build high-performing teams, and design products people love. But we are more than a platform-we are the creators and stewards of the Experience Management category serving over 18K clients globally. Building a category takes grit, determination, and a disdain for convention-but most of all it requires close-knit, high-functioning teams with an unwavering dedication to serving our customers. When you join one of our teams, you'll be part of a nimble group that's empowered to set aggressive goals and move fast to achieve them. Strategic risks are encouraged and complex problems are solved together, by passing the mic and iterating until the best solution comes to light. You won't have to look to find growth opportunities-ready or not, they'll find you. From retail to government to healthcare, we're on a mission to bring humanity, connection, and empathy back to business. Join over 5,000 people across the globe who think that's work worth doing. Staff Data Scientist: Semantic Substrate Incubation Why We Have This Role At Semantic Substrate Incubation, we are drowning in data but starving for meaning. As our lead data scientist, you will bridge this "Meaning Gap" by turning raw, chaotic event logs into an intelligent, concept-linked graph-the Semantic Brain. You will move past basic chat interfaces to architect an Identity-Anchored World Model that allows LLMs to understand complex enterprise ideas like "High-Value Churn Risk" and drive autonomous, agentic decisions. Working alongside a tight-knit team of researchers and production engineers, your work will directly define how the next generation of AI comprehends the business world. How You'll Find Success Thrives in Ambiguity: Operates with a zero-to-one startup mentality. You don't need a map; you look at complex, unstructured data chaos and naturally enjoy building foundational AI products and data pipelines from scratch. Bridges Science and Engineering: Fluidly moves between deep applied AI research and robust production engineering, ensuring brilliant theories actually scale in production. Customer-Centric Translator: Enjoys working directly with pilot partners and customers, listening to their unique business pain points, and translating them into technical requirements and concrete industry ontologies. Principled Technical Leader: Takes ownership of the technical vision, setting a high bar for architectural excellence while mentoring and elevating the engineering team around you. Rigorous and Evidence-Driven: Rejects guesswork. You lean heavily on simulation, validation, and off-policy evaluation to ensure AI recommendations are grounded in reality. How You'll Grow Pioneer Agentic AI: You will be at the absolute bleeding edge of LLM orchestration and world modeling, setting industry standards for how enterprises deploy autonomous agents. Expand Technical Authorship: Refine your voice as an industry thought leader with active support to publish papers, write technical books, or speak at major global AI conferences. Executive & Strategic Visibility: Shape the foundational AI product roadmap of the company, giving you direct influence over strategic business decisions and high-level customer relationships. Things You'll Do Map fragmented data to human-readable terms by leading the discovery and mapping of raw event logs to Vertical Ontologies (Industry Knowledge Packs). Accelerate AI accuracy by 60% by designing and deploying a Concept Graph that anchors the substrate, utilizing verified profile IDs instead of session data for memory. Train autonomous agents efficiently by building the logic for Reward Signal Extraction and Context-Aware actioning to infer KPIs directly from interaction logs, avoiding traditional delayed-reward bottlenecks. Reduce agentic action risk by 40% by utilizing Off-Policy Evaluation (OPE) and action-conditional world models to simulate high-value scenarios and ground recommendations. Avoid the "Services Trap" and enable scale by engineering automated systems that allow 80% of the team's context mapping to be executed seamlessly without manual intervention. What We're Looking For On Your Resume A Proven Tracker Record in AI/ML: Broad capability delivering high-impact AI systems at scale (typically requires around 10+ years of professional data science experience). Deep Graph Expertise: Hands-on experience designing, implementing, and querying graph databases, with specific, deep technical proficiency in AWS Neptune and SPARQL. Production-Level Data Pipelines: Extensive experience with Apache Spark (PySpark/Scala) for large-scale distributed data processing and ETL optimization on massive datasets. Modern LLM Orchestration: Direct, practical experience building sophisticated applications using frameworks like LangChain, LlamaIndex, or equivalent agentic workflows. Cloud Architecture: Strong hands-on b

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