Job Overview
Location
San Francisco
Job Type
Full-time
Category
Data Science
Date Posted
June 4, 2026
Full Job Description
đź“‹ Description
- • Lead and scale Scribe’s Product Analytics and Data Engineering teams, driving strategy and roadmap for reporting, data-powered insights, and experimental design to amplify the data platform and product development.
- • Build and foster a high-performing data culture centered on hypothesis-driven experimentation, continuous learning, and bias to action, ensuring teams make fast, informed decisions that fuel product investments.
- • Serve as a cross-functional partner to product, growth, marketing, and sales teams, analyzing data from Scribe’s 5M+ users to generate actionable insights that drive strategic business impact and improve customer experience.
- • Define and deliver on Scribe’s data platform strategy, aligning data initiatives with organizational goals and integrating them into executive-level strategic efforts.
- • Hire, develop, and retain top talent in data analytics, data engineering, and data science, with a focus on cultivating low-ego, proactive, impact-driven professionals who roll up their sleeves to deliver results.
- • Establish and maintain the semantic/metrics layer as the single source of truth used by both humans and natural-language agents, ensuring consistency and reliability across all data-driven decision-making.
- • Design and implement the technical infrastructure to power agentic automation on top of the data platform, enabling scalable, AI-driven insights and operational efficiency.
- • Continuously evaluate and integrate new technologies to advance data modeling, data governance, and team capabilities, improving data accessibility and operational efficiency across the organization.
- • Balance quantitative data with qualitative insights to inform product and business strategy, ensuring decisions are grounded in both metrics and user context.
- • Prioritize outcomes over output, directing teams toward high-impact data processes while also being willing to perform quick, actionable analyses (e.g., napkin math) to accelerate decision-making.
- • Drive operational efficiency by eliminating data silos and ensuring data is leveraged effectively by all business functions, from finance to sales.
- • Maintain a customer-centric mindset, using data to understand customer journeys, product engagement patterns, and growth trends to optimize the user experience.
- • Champion data as a revenue driver, not a cost center, ensuring the data team’s work directly contributes to business growth and OKR achievement.
- • Collaborate with executive leadership to embed data initiatives into the core of Scribe’s strategic planning and execution.
🎯 Requirements
- • 10+ years of experience working on data teams powering products that customers love
- • 4+ years of experience hiring and managing high-performing data analysts, data engineers, and data scientists
- • Strong technical proficiency with the Modern Data Stack, including Snowflake, dbt, Sigma, and Mixpanel
- • Experience building the semantic/metrics layer that serves as the single source of truth for humans and natural-language agents
- • Proactive, impact-driven mindset with a bias toward action and outcomes over output
- • Low ego, with willingness to engage in hands-on work and lead data projects from the trenches
🏖️ Benefits
- • Comprehensive healthcare
- • Equity in a hypergrowth startup
- • Flexible PTO
- • 401k
- • Parental Leave
- • Commuter Benefits (for SF office employees)
- • WFH Office Stipend
Skills & Technologies
About Scribe
ScribeHow.com is the fastest way to turn any process into a step-by-step visual guide. Our AI screen recorder watches your workflow, auto-writes crystal-clear instructions, adds annotated screenshots, and publishes a branded, shareable how-to in minutes. Replace endless Zoom walk-throughs, stale PDFs, and ticket backlogs with living docs that customers, teammates, and new hires can replay, search, and translate instantly. Built for SaaS onboarding, SOPs, support, and training, ScribeHow slashes ramp-up time, cuts support volume, and keeps knowledge always up to date so teams scale without slowing down.
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