Staff Data Scientist - Product Analytics

Build AI contracting at enterprise scale. Ship it fast.
Ironclad is building AI on one of the most consequential datasets in enterprise software: over 2 billion contracts across thousands of the world's largest organizations. Contracts run every dollar, deal, and business relationship on the planet, and the AI transformation of this space is still largely uncharted. Engineers here are building agentic solutions to problems that haven't been solved yet, in a category that's still being defined. The feedback loop is short, the data is rich, and the people closest to the work are the ones deciding what gets built next. That ability to deliver impact quickly is why the the companies at the forefront of AI choose Ironclad to manage their contracts.
We’re consistently recognized as a leader in the industry: a Leader in the Forrester Wave and Gartner Magic Quadrant for Contract Lifecycle Management, a Fortune Great Place to Work, and one of Fast Company’s Most Innovative Workplaces. Ironclad has also been named to Forbes’ AI 50 and Business Insider’s list of Companies to Bet Your Career On. We’re backed by leading investors including Accel, Y Combinator, Sequoia, BOND, and Franklin Templeton. For more information, visit www.ironcladapp.com or follow us on LinkedIn.

This is a hybrid role. Office attendance is required at least twice a week on Tuesdays and Thursdays for collaboration and connection. There may be additional in-office days for team or company events.

About the Role
As a Staff Product Analytics Data Scientist, you will be the analytical backbone of how Ironclad understands, measures, and improves its product. You'll turn raw product usage and contract data into a deep, quantitative understanding of how customers adopt our platform and our AI and you'll translate that understanding into decisions that shape the roadmap.
This is a builder's role. Our team owns its own data end to end: we model and maintain our own dbt pipelines, mine large and messy datasets for signal, and partner closely with Product and Engineering to ship data products that put insight directly into customers' and teammates' hands. You'll wear a product analytics hat most days, an analytics engineering hat when the pipeline needs it, and a data science hat when a problem calls for experimentation, causal inference, or modeling. As a Staff-level individual contributor, you'll set analytical direction, raise the technical bar across the team, and influence senior stakeholders without formal authority.

What You'll Do
Own product understanding. Define, instrument, and analyze the metrics that describe how customers adopt, retain, and get value from Ironclad—funnels, activation, feature adoption (including our AI features like Jurist), engagement, and retention—and make them trustworthy and self-serve.

Drive experimentation and causal analysis. Design and analyze A/B tests and quasi-experiments; apply causal inference where clean experiments aren't possible; and give Product and Engineering clear, defensible reads on what actually moved the needle.

Mine data for opportunity. Explore large, complex product and contract datasets to surface non-obvious patterns, quantify opportunities, and generate hypotheses that shape strategy—not just answer questions that were already asked.

Build and evolve data products. Partner with Product and Engineering to turn analysis into shipped features—embedded analytics, benchmarks, insights, and AI-powered experiences—that deliver value directly to customers and internal teams.

Wear the analytics engineering hat. Own and extend the dbt models and transformations that power your work. Because our team owns its pipelines, you'll design scalable, well-documented, well-tested data models and uphold consistent definitions across the warehouse and BI layer.

Architect AI-ready data. Leverage AI to accelerate your own pipeline and analysis work, and structure our data assets, documentation, and metadata so that bo