Head of Data

About the role

As the Head of Data, you'll lead and grow our Product Analytics and Data Engineering teams, by driving the strategy and roadmap for reporting, data-powered insights, and experimental design that will amplify our data platform and product development. You'll build teams and tools that empower Scribe to make informed decisions at every level, enabling step changes for our business. Working closely with product, growth, marketing, and sales, you will analyze the data from Scribe's 5M+ users and suggest actionable insights that drive strategic business impact. Your work will be central to advancing Scribe's mission, helping us boost OKRs and deliver a top-tier customer experience. Key responsibilities of this role include: Manage and grow a high-performing data team by hiring and developing talent, fostering a culture of experimentation, continuous learning, and bias to action. Define and deliver on Scribe's data platform , aligning with our organizational goals and working with executive leadership to integrate data initiatives into strategic company efforts. Be a cross-functional magnet with our business and finance teams, to gather insights on customer journeys, product engagement, and growth trends, ensuring data is leveraged effectively by everyone. Continuously evaluate and integrate new technologies to advance data modeling, data governance, and team capabilities, driving operational efficiency and data accessibility across Scribe. What makes you a great fit: Have 10+ years of experience working on Data teams powering products that customers love Have 4+ years of experience in hiring and managing high-performing data analysts, data engineers, and data scientists Strong technical proficiency in our tech stack - Snowflake, Sigma, Mixpanel, dbt cloud, and Looker Customer mindset , adept at balancing quantitative data with qualitative insights to drive product and business strategy decisions Low ego. You care about building things and recognize that this may require rolling your sleeves up, getting in the trenches, and occasionally leading data projects Proactive impact-driven. You push insights and data onto teams rather than waiting for requests to emerge from them Outcomes over output. You thrive on creating business value and know when to point your team to a multi-step data process v/s doing ugly napkin math to bias towards action Experience building technical and semantic infrastructure to power internal natural language agents and agentic automation Bonus Points Experience working in high-paced Enterprise SaaS startups, with a strong self-serve motion Experience creating a step-function change in an organization's data strategy with the help of AI tooling Experience deploying machine learning models in Production About Scribe Scribe is where exceptional people come to do the best work of their careers. More than 94% of the Fortune 500 use Scribe to ensure work gets done right, and see how to do it even better. Our Workflow AI platform automatically captures and optimizes workflows so teams work smarter, faster, and more consistently. We're growing fast - since our founding in 2019, we've grown to over 5 million users across 600,000 businesses. Based in San Francisco, we've been named a LinkedIn Top Startup, are valued at over $1 billion, and are backed by leading investors. Join us in our mission to uplevel how people do work. Full-Time US Employee Benefits Include Comprehensive healthcare Equity in a hypergrowth startup Flexible PTO 401k Parental Leave Commuter Benefits (SF office employees) WFH Office Stipend Our HQ is in beautiful San Francisco, California. For this role, we expect you to commute and work from the office roughly 3 days per week.

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Additional Information

tl;dr - At Scribe, data is the foundation of how we make decisions - we take it very seriously . We've built a data-literate team, where each function does hypothesis-driven experimentation with clear, measurable outcomes. Our data layer is treated as a revenue driver for the business, and not a cost center. We're looking for a leader to manage and scale the data analytics and data engineering teams, while maintaining a focus on empowering our product team to make fast, informed decisions that fuel the next generation of product investments.

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