Staff Data Scientist: Semantic Substrate Incubation

Qualtrics • Seattle, WA

7d • $206,500 - $271,000 • Hybrid

About The Position

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.

Requirements

• Broad capability delivering high-impact AI systems at scale (typically requires around 10+ years of professional data science experience).
• Hands-on experience designing, implementing, and querying graph databases, with specific, deep technical proficiency in AWS Neptune and SPARQL.
• Extensive experience with Apache Spark (PySpark/Scala) for large-scale distributed data processing and ETL optimization on massive datasets.
• Direct, practical experience building sophisticated applications using frameworks like LangChain, LlamaIndex, or equivalent agentic workflows.
• Strong hands-on backend and infrastructure skills utilizing Python and the AWS ecosystem (EC2, Lambda, S3, CloudFormation, CDK, or Terraform).

Nice To Haves

• 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.
• Fluidly moves between deep applied AI research and robust production engineering, ensuring brilliant theories actually scale in production.
• 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.
• Takes ownership of the technical vision, setting a high bar for architectural excellence while mentoring and elevating the engineering team around you.
• Rejects guesswork. You lean heavily on simulation, validation, and off-policy evaluation to ensure AI recommendations are grounded in reality.

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, 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.

Benefits

• Dedicated Growth Time: We spend 10% of our time every quarter on individual engineering growth activities, research exploration, and passion projects.
• Continuous Learning Stipend: Receive an annual stipend for technical books, research papers, and subscriptions to keep your skills at the absolute cutting edge.
• Conference & Publication Support: Fully covered travel and attendance expenses when you are selected to present research or speak at major industry AI conferences.
• Top-Tier Health & Wellness: Comprehensive global health, dental, and vision coverage, alongside flexible time-off policies to ensure you stay energized.
• medical, dental, vision, life and disability, 401(k) with match, paid time off, a wellness reimbursement, mental health benefits, and an experience bonus.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Education Level: No Education Listed