The job, in the employer's words
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 both humans and LLMs can navigate them with high confidence and minimal hallucination.
Set the bar and mentor. Provide technical direction, code and analysis reviews, and mentorship to analysts, data scientists, and analytics engineers—fostering a culture of rigor, collaboration, and impact.
Influence senior stakeholders. Bring clarity to ambiguous, high-stakes product questions and communicate findings in a way that drives alignment and action across Product, Engineering, and leadership.
Self-serve enablement: Design and scale self-serve analytics ecosystems, semantic layers, and clear data documentation that empower non-technical stakeholders to answer their own data questions with confidence.
What We're Looking For
8+ years of experience in product analytics, data science, or a closely related quantitative field, including demonstrated impact at a senior or staff level (ideally at a B2B SaaS company).
Deep expertise in product analytics: experimentation and A/B testing, funnel and retention analysis, causal inference, and defining product metrics that stand up to scrutiny.
Advanced SQL, plus fluency in Python or R for analysis, statistics, and modeling.
You can own dbt models, data modeling, and ELT best practices, and you're comfortable being the person who fixes the pipeline rather than filing a ticket.
A track record of partnering with Product and Engineering to ship data products or data-informed features, not just deliver dashboards and reports.
Strong data mining and exploratory instincts: you find the signal in large, messy datasets and know which findings are worth acting on.
Experience (or strong interest) in AI-assisted development and "AI-ready" data—using tools like Cursor or Claude Code, and writing documentation and metadata that help humans and LLMs work with data reliably.
Familiarity with a modern data stack such as Segment, Fivetran, BigQuery, dbt, Airflow, Looker, and exploration tools like Hex (or their equivalents).
A self-starter who leads initiatives end to end, communicates with clarity, and bridges technical work and business impact.
Base Salary Range: $180,000 - $220,000 offers company bonus
The base salary range represents the minimum and maximum of the salary range for this position based at our San Francisco headquarters. The actual base salary offered for this position will depend on numerous factors, including individual proficiency, anticipated performance, and the location of the selected candidate. Our base salary is just one component of Ironclad’s competitive total rewards package, which also includes equity awards (a new hire grant, along with opportunities for additional awards throughout your tenure), competitive health and wellness benefits, and a commitment to career growth and development.
US Full-Time Employee Benefits at Ironclad:
100% health coverage for employees (medical, dental, and vision), and 75% coverage for dependents with buy-up plan options available
Market-leading leave policies, including gender-neutral parental leave and compassionate leave
Family forming support through Maven for you and your partner
Paid time off - take the time you need, when you need it
Monthly stipends for wellbeing, hybrid work, and (if applicable) cell phone use
Mental health support through Modern Health, including therapy, coaching, and digital tools
Pre-tax commuter benefits (US Employees)
401(k) plan with Fidelity with employer match (US Employees)
Regular team events to connect, recharge, and have fun
And most importantly: the opportunity to help build the company you want to work at
**UK Employee-specific benefits are included on our UK job postings
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Benefits mentioned
- 100% health coverage for employees (medical, dental, and vision), and 75% coverage for dependents with buy-up plan options available
- Market-leading leave policies, including gender-neutral parental leave and compassionate leave
- Family forming support through Maven for you and your partner
- Paid time off - take the time you need, when you need it
- Monthly stipends for wellbeing, hybrid work, and (if applicable) cell phone use
- Mental health support through Modern Health, including therapy, coaching, and digital tools
- Pre-tax commuter benefits (US Employees)
- 401(k) plan with Fidelity with employer match (US Employees)
- Regular team events to connect, recharge, and have fun
- And most importantly: the opportunity to help build the company you want to work at
- **UK Employee-specific benefits are included on our UK job postings
- Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Requirements mentioned
- 8+ years of experience in product analytics, data science, or a closely related quantitative field, including demonstrated impact at a senior or staff level (ideally at a B2B SaaS company).
- Deep expertise in product analytics: experimentation and A/B testing, funnel and retention analysis, causal inference, and defining product metrics that stand up to scrutiny.
- Advanced SQL, plus fluency in Python or R for analysis, statistics, and modeling.
- You can own dbt models, data modeling, and ELT best practices, and you're comfortable being the person who fixes the pipeline rather than filing a ticket.
- A track record of partnering with Product and Engineering to ship data products or data-informed features, not just deliver dashboards and reports.
- Strong data mining and exploratory instincts: you find the signal in large, messy datasets and know which findings are worth acting on.
- Experience (or strong interest) in AI-assisted development and "AI-ready" data—using tools like Cursor or Claude Code, and writing documentation and metadata that help humans and LLMs work with data reliably.
- Familiarity with a modern data stack such as Segment, Fivetran, BigQuery, dbt, Airflow, Looker, and exploration tools like Hex (or their equivalents).
- A self-starter who leads initiatives end to end, communicates with clarity, and bridges technical work and business impact.
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