Staff Data Scientist - Product Analytics

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. You'll translate that understanding into decisions that shape the roadmap. This is a builder's role where the team owns its data end-to-end: modeling and maintaining dbt pipelines, mining large datasets for signal, and partnering with Product and Engineering to ship data products that deliver insights directly to customers and teammates.

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.

Responsibilities

• Own product understanding: Define, instrument, and analyze metrics describing customer adoption, retention, and value—funnels, activation, feature adoption (including 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; provide clear, defensible reads on what 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.
• Build and evolve data products: Partner with Product and Engineering to turn analysis into shipped features—embedded analytics, benchmarks, insights, and AI-powered experiences for customers and internal teams.
• Wear the analytics engineering hat: Own and extend dbt models and transformations, design scalable, well-documented data models, and uphold consistent definitions across the warehouse and BI layer.
• Architect AI-ready data: Leverage AI to accelerate pipeline and analysis work, and structure data assets, documentation, and metadata for high confidence and minimal hallucination by humans and LLMs.
• Set the bar and mentor: Provide technical direction, code and analysis reviews, and mentorship to analysts, data scientists, and analytics engineers.
• Influence senior stakeholders: Bring clarity to ambiguous, high-stakes product questions and communicate findings to drive alignment and action across Product, Engineering, and leadership.
• Self-serve enablement: Design and scale self-serve analytics ecosystems, semantic layers, and clear data documentation to empower non-technical stakeholders.

Requirements

• 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.
• Ability to own dbt models, data modeling, and ELT best practices; comfortable fixing pipelines rather than filing tickets.
• 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: find signal in large, messy datasets and identify actionable insights.
• Experience (or strong interest) in AI-assisted development and "AI-ready" data—using tools like Cursor or Claude Code, and writing documentation for humans and LLMs.
• Familiarity with a modern data stack such as Segment, Fivetran, BigQuery, dbt, Airflow, Looker, and exploration tools like Hex (or equivalents).
• A self-starter who leads initiatives end-to-end, communicates with clarity, and bridges technical work and business impact.

Pay

Base Salary Range: $180,000 - $220,000. The range represents the minimum and maximum for this position based at our San Francisco headquarters. The actual base salary offered will depend on factors including individual proficiency, anticipated performance, and location. This role also includes a company bonus and equity awards (new hire grant plus opportunities for additional awards).

Schedule

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

Benefits

• 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.