GTM Data Analyst

Overview About Clay: Our mission is to help organizations turn any growth idea into reality. We see growth as a creative practice, not a formula. Finding and reaching your best-fit customers takes unique ideas and constant iteration. As AI makes execution faster and tactics easier to copy, creativity is the only lasting advantage. We\'re already helping thousands of customers — including Anthropic, Notion, Google, and Ramp — go to market with unique data, signals, and AI research. In 2025, we crossed $100M in revenue and raised a $100M Series C at a $5B valuation, backed by world-class investors including Sequoia, CapitalG, and First Round. We also completed our second employee tender offer and launched a community equity round, for our customers, agency partners, and club members. Some things to know about us: Our community includes 11,000+ customers, 150+ integration partners, 125+ agencies, 50+ Clay clubs, and 30k members on Slack. Our culture is unique inside and outside of work. Our team members are also DJs, activists, writers, clowns, marathoners, skydivers, psychedelic therapists, social workers, and more. All employees can work for free with world-class coaches who specialize in creativity, management, and more. Our operating principles — including negative maintenance and non-attached action — guide our work. Read about us in the NYT, Forbes, First Round Review, and more. Hear from our employees directly on our Glassdoor page! GTM Data Scientist — role context We’re looking for a GTM Data Scientist to help make Clay data-driven from the ground up. You’ll join a team of experienced data scientists and analytics engineers, while partnering closely with Product and Go-to-Market teams to build foundational data models, dashboards, and analyses that teams rely on every day. This role is ideal for someone early in their data career who wants to learn quickly from senior teammates, take on meaningful ownership from day one, and do that work inside one of the fastest-growing AI startups while digging deeply into data to understand why things are happening, not just what is happening. What you’ll do Build and own analytics data models Write clean, maintainable SQL against Snowflake to power core metrics, dashboards, and analytical workflows. Build and iterate on analytics metrics and tables Build and iterate on metrics and tables in dbt, and surface them through dashboards in Sigma to help teams understand product usage, performance, and change over time. Explore data deeply to answer open-ended questions Use SQL as your primary tool, with Python or R in a notebook environment like Hex when helpful, to investigate trends, anomalies, and product behavior and connect analyses back to real business questions. Help operationalize data Support reverse ETL workflows using Census, helping make modeled data actionable in the tools teams use day-to-day. Translate questions into insight Partner with cross-functional teams to turn ambiguous questions into clear, useful analytical outputs. What we’re looking for Strong SQL fundamentals — comfortable with joins, CTEs, window functions, and clear query structure Experience building analytical data models or metrics tables using dbt or similar analytics-engineering workflows Comfortable working with BI tools like Sigma, Looker, Tableau, Mode, or similar Strong analytical intuition — able to ask the right questions, explore data thoughtfully, and synthesize clear, well-reasoned conclusions Clear communicator who can share insights with technical and non-technical partners Deeply curious about product usage and business performance — motivated to go beyond the what to understand the why, without getting lost in rabbit holes Nice to have Experience with Snowflake or other similar cloud data warehousing tools Comfortable using SQL as the primary analysis tool, with the ability to use Python or R when helpful for deeper or more efficient analysis Familiarity with Hex or other notebook-based analysis tools Familiarity with Census or other reverse ETL tools Prior experience in a product-led or B2B SaaS environment Compensation Range: $130K - $170K #J-18808-Ljbffr