Staff Data Scientist

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.

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.