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Lead Pricing Strategist

GitLab - Remote - Remote - posted 2026-08-27

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GitLab is seeking a Pricing Strategist to shape pricing and packaging strategy across its portfolio, including Premium and Ultimate tiers, GitLab Duo, and emerging AI and usage-based products like Flex and Orbit. You will collaborate with leaders across Product Management, Product Marketing, Finance, go-to-market teams, Sales, and Deal Desk to evaluate opportunities, create business models for new offerings, and improve existing portfolio packaging. Key responsibilities include analyzing market trends, competitor pricing, and customer usage data to make evidence-based pricing recommendations. You'll use structured problem-solving to form hypotheses, complete analysis, validate findings, and recommend actions. You'll conduct regular pricing reviews to identify opportunities and help execute plans to address them. As GitLab's portfolio evolves, especially in AI, credit-based pricing, and usage-based products, you'll evaluate new business models and monetization approaches. You'll partner with product and fulfillment teams to prioritize launches and map new SKUs to correct products and feature sets. You'll monitor pricing and packaging changes post-launch and apply learnings to ongoing strategy. Clear communication is essential—you'll need to influence senior leaders and build alignment across stakeholders with competing priorities. You bring significant experience leading SaaS pricing strategy and analysis across products or complex portfolios. You have strong financial analysis and modeling skills, with proficiency in data and business intelligence tools like Sisense or Tableau. You excel at turning complex data into clear, practical recommendations and framing ambiguous problems to facilitate executive decisions. You communicate credibly with different audiences, influence senior management, and maintain alignment across cross-functional stakeholders while managing multiple projects and competing deadlines. You're intellectually curious and comfortable working through ambiguity in a fast-paced, iterative environment.

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