Principal Data Scientist, Knowledge Engineering, Customer Success Data Platform

Intuit

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Quick summary

Work type
On-site
Location
Mountain View, CASan Diego, CA
Salary
$247,500–$335,000 / yr
Posted
3 days ago
Freshness
Confirmed live today

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $176k
This role $291k
$106k $359k
below market most similar roles pay here above market

This role pays more than 98% of similar roles. Most pay $143,551–$208,800 — the blue band above. At the midpoint, this role pays about $291k versus about $176k for comparable roles.

Based on 240 similar postings.

Employer

About Intuit

Intuit is a financial software company known for products like TurboTax, QuickBooks, Mint, and Credit Karma, helping consumers and small businesses manage their finances and taxes. Industry: Financial Software & Technology

Intuit currently has 255 open roles on FindRole.

Listed pay typically runs $202,500–$274,000 across 236 roles with salary data.

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At a glance

TL;DR · Principal Data Scientist, Knowledge Engineering, Customer Success Data Platform

The Principal Data Scientist - Knowledge Engineering, Customer Success Data Platform joins the Intuit Customer Success team to architect the knowledge and agentic intelligence foundation. This role involves defining the knowledge architecture, governance, and semantic layer strategy for the ICS data platform. You will build and prototype agentic intelligence systems, including the Intuit Customer Success Knowledge Graph, to power internal agent experiences and self-serve data agents. Key responsibilities include designing ontologies, entity resolution, and hybrid retrieval patterns like GraphRAG. You will utilize technologies such as Neo4j, Neptune, Databricks, Snowflake, AWS, LangGraph, and LlamaIndex. The role requires deep expertise in knowledge modeling, LLM-powered systems, and production-quality coding to solve complex problems regarding knowledge quality, lineage, and responsible AI in a regulated domain.

What does a Data Scientist earn in California?

Median $214500 from 117 postings across 27 companies.

See salary data

What you'll do

  • Define and own the knowledge architecture, ontologies, and taxonomies for the ICS data platform.
  • Architect the agentic intelligence layer, including GraphRAG, hybrid retrieval, and multi-agent orchestration.
  • Establish the semantic layer strategy to ensure consistent business metrics across all AI experiences.
  • Build a governance strategy for knowledge quality, lineage, provenance, and responsible AI.
  • Evaluate and select core technologies such as graph stores, vector stores, and agent frameworks.
  • Write production-quality code to build prototypes and solve the hardest technical problems.
  • Develop evaluation frameworks to measure knowledge coverage, retrieval quality, and agent reliability.
  • Mentor data scientists and engineers while raising the technical bar through design reviews.

What we're looking for

  • 15+ years in data and knowledge engineering, or AI and ML engineering, including significant time as a technical lead or architect.
  • Proven track record of architecting and shipping large-scale data and knowledge systems in production.
  • Deep expertise in knowledge modeling, including ontology and taxonomy design, entity resolution, and graph data modeling.
  • Hands-on experience building LLM-powered and agentic systems, including RAG, GraphRAG, and agent frameworks.
  • Deep knowledge of AI infrastructure, including vector and graph databases, embedding pipelines, and cloud data platforms.
  • Experience defining semantic layer strategies and designing data and knowledge governance for lineage, quality, and responsible AI.
  • Strong programming skills with the ability to write and review production-quality code.
  • BS in Computer Science, Data Science, Statistics, Information Science, or a related field (MS or PhD preferred).

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