Staff Data Scientist - AI

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. 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 our team, you’ll be part of a nimble group empowered to set aggressive goals and move fast to achieve them. Strategic risks are encouraged, and complex problems are solved collaboratively by iterating until the best solution emerges.

About the 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 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 build foundational AI products and data pipelines from scratch using complex, unstructured data.
• Bridges Science and Engineering: Moves fluidly between deep applied AI research and robust production engineering, ensuring theories scale in production.
• Customer-Centric Translator: Works directly with pilot partners and customers to translate business pain points into technical requirements and industry ontologies.
• Principled Technical Leader: Owns the technical vision, sets a high bar for architectural excellence, and mentors the engineering team.
• Rigorous and Evidence-Driven: Rejects guesswork; relies on simulation, validation, and off-policy evaluation to ground AI recommendations in reality.

How you’ll grow

• Pioneer Agentic AI: Work at the bleeding edge of LLM orchestration and world modeling, setting industry standards for enterprise autonomous agents.
• Expand Technical Authorship: Refine your voice as an industry thought leader with support to publish papers, write technical books, or speak at global AI conferences.
• Executive & Strategic Visibility: Shape the foundational AI product roadmap, influencing strategic business decisions and high-level customer relationships.

Responsibilities

• 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 using verified profile IDs instead of session data.
• Train autonomous agents efficiently by building logic for Reward Signal Extraction and Context-Aware actioning to infer KPIs directly from interaction logs.
• Reduce agentic action risk by 40% using Off-Policy Evaluation (OPE) and action-conditional world models to simulate high-value scenarios.
• Avoid the "Services Trap" by engineering automated systems that allow 80% of context mapping to be executed without manual intervention.

Requirements

• Proven Track Record in AI/ML: Broad capability delivering high-impact AI systems at scale (typically 10+ years of professional data science experience).
• Deep Graph Expertise: Hands-on experience designing, implementing, and querying graph databases, with 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.
• Modern LLM Orchestration: Practical experience building applications using frameworks like LangChain, LlamaIndex, or equivalent agentic workflows.
• Cloud Architecture: Strong backend and infrastructure skills using Python and AWS (EC2, Lambda, S3, CloudFormation, CDK, or Terraform).

About the team

• We Build From Scratch: A true zero-to-one incubation team; rapid prototyping and immediate impact without bureaucracy.
• Unmatched Autonomy: Freedom to steer the technical direction of the Semantic Substrate without micromanagement.
• Collaboration Over Silos: Fluid work across applied research, data engineering, and product—no throwing code over the wall.
• Obsessed with Ground Truth: Focused on solving the deepest technical challenges in enterprise AI with academic rigor.

Benefits

• Dedicated Growth Time: 10% of time each quarter for individual engineering growth, research, and passion projects.
• Continuous Learning Stipend: Annual stipend for technical books, research papers, and subscriptions.
• Conference & Publication Support: Fully covered travel and attendance for presenting research or speaking at major AI conferences.
• Top-Tier Health & Wellness: Comprehensive global health, dental, and vision coverage, with flexible time-off policies.

Schedule

Hybrid work model: Three days in the office (Mondays, Thursdays, and one day selected by your organizational leader) with the rest of the week remote.

Pay

Washington State base annual pay range: $206,500—$271,000 USD. Full-time positions include a sign-on bonus, restricted stock units, medical/dental/vision/life/disability benefits, 401(k) with match, paid time off, wellness reimbursement, mental health benefits, and an experience bonus.