Staff Data Scientist

Intuit • San Diego, CA • 15h ago

Overview

We're seeking a Staff Data Scientist to lead the development of a next-generation AI-native analytics platform that transforms how Intuit synthesizes insights from structured and unstructured data. This internal-facing platform is designed to power real-time decision-making across multiple business units by drastically accelerating time-to-insight, improving analytical consistency, and minimizing the manual burden of data synthesis.

This role calls for a deeply technical, strategic, and collaborative leader who thrives at the intersection of data science, backend engineering, and AI innovation. You will own the end-to-end design and implementation of this solution, which will ingest signals from a variety of data sources-transaction logs, clickstream data, operational systems, Slack, JIRA, and more-and convert them into digestible narratives, dashboards, and data products that power executive and operational decisions.

What you'll bring

Demonstrated ability to independently drive large-scale analytics or AI systems from conception to production.

Deep expertise in Python, SQL, and data tooling with ability to work across structured and semi/unstructured data.

Familiarity with microservices architecture, container orchestration (Kubernetes), and scalable infrastructure.

Advanced modeling skills in both traditional ML and Generative AI, particularly with open-source or custom LLMs.

Experience in web experimentation frameworks and statistical analysis methodologies.

Strong storytelling and executive influence capability through data.

Nice-to-Have :

Prior experience in cross-functional enterprise platforms or data products used by analysts, product managers, or operations teams.

Background in customer support analytics or diagnostic tooling across service platforms.

Experience deploying systems that interact with chat logs, documentation, or metrics across diverse internal tooling ecosystems.

Impact Scope

The analytics platform you build will:

Accelerate time-to-insight by over 95%, reducing multi-day data gathering and synthesis workflows to under 5 minutes.

Act as a force multiplier for analysts and data scientists, enabling scalable support across teams.

Support decision-making by automatically assembling narratives and dashboards from distributed data fragments-across BI tools, operational logs, conversational data, and mor

How you will lead

Lead End-to-End Data Science Projects

Architect and build an enterprise-grade analytics system capable of querying, interpreting, and narrating insights from large volumes of fragmented data sources.

Lead development from initial scoping and experimentation to deployment of a production-grade, Kubernetes-native microservice.

Drive AI-Native Solutions

Design solutions using LLM architectures, retrieval-augmented generation (RAG), and multi-agent orchestration frameworks.

Translate business needs into intelligent agents that can autonomously identify KPIs, root causes, anomalies, and trends across datasets.

Shape Experimentation & Causal Inference

Lead the development of advanced experimentation systems including A/B/n tests, bandits, and painted-door experiments.

Apply and guide the use of causal inference techniques (e.g., Propensity Score Matching, Difference-in-Differences, Synthetic Controls) to measure outcomes and inform decision-making.

Influence Strategic Decision-Making

Serve as a thought leader to define analytical workflows that minimize time-to-insight and maximize actionability across business segments.

Influence leaders across product, operations, and data teams using clearly synthesized, high-impact insights.

EOE AA M/F/Vet/Disability. Intuit will consider for employment qualified applicants with criminal histories in a manner consistent with requirements of local law.

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