Responsibilities

• Analyze marketing, pipeline, and revenue performance to surface trends, risks, opportunities, and the drivers behind them
• Conduct deep-dive analyses to answer the ambiguous business questions that don't fit in a dashboard
• Translate data into clear, actionable recommendations for marketing leadership
• Tell the org not just what happened, but why it happened and what to do next
• Build scalable frameworks for measuring marketing effectiveness across channels, campaigns, and funnel stages
• Partner with Marketing Ops, RevOps, and BI to evolve our marketing data ecosystem into something scalable, trustworthy, and analysis-ready
• Improve the quality, accessibility, and consistency of marketing performance data
• Identify gaps, inefficiencies, and structural problems in how we measure, and lead the work to fix them
• Support forecasting, pacing, and pipeline analysis across the marketing org
• Analyze funnel conversion trends, investment efficiency, and performance drivers

Requirements

• 3+ years in marketing analytics, marketing intelligence, data science, or related analytical roles
• Strong SQL and hands-on data analysis. You don't need someone to pull the number for you
• Experience with BI and visualization platforms: Tableau, Looker, Power BI, or equivalents
• Familiarity with CRM, marketing automation, and modern data warehouse environments
• AI-native. You use Claude, ChatGPT, and the rest of the stack to do more, faster, every day
• Excellent business judgment. You know when to push a model further and when to ship the answer
• Strong communication. You can write a finding the way a journalist writes a headline: clear, sharp, undeniable
• Comfortable operating in ambiguous, fast-moving environments

Preferred

• B2B SaaS or GTM analytics experience
• Cross-functional work with RevOps, Finance, and Marketing leadership
• Attribution modeling, funnel analysis, forecasting, or investment modeling experience
• Exposure to modern data stack environments and analytics engineering concepts
• Predictive analytics or statistical modeling background

Benefits

• 🍏 Health: Multiple health plan options to suit your needs, including medical, dental, vision, and telemedicine coverage
• 💼 Insurance: Life, disability, and supplemental indemnity plans
• ⚖️ Work-Life Balance: Flexible Time Off for salaried employees, PTO for hourly employees, Paid Sick Time, Paid Parental Bonding Leave, and holiday pay
• 💰 Financial Security: 401(k) with company match, Health Savings Accounts with company contributions, Dependent Care FSA
• 🤸‍ Wellness: Employee Assistance Program (EAP) and comprehensive wellness initiatives
• 🌱 Growth: Access to ongoing learning and development opportunities and career advancement