Compensation Analytics Manager
OpenAIRemotePosted 11 February 2026
Job Description
About the TeamOpenAI’s Compensation group sits within Total Rewards and plays a foundational role in attracting, rewarding, and retaining world-class talent in support of our mission to ensure artificial general intelligence benefits all of humanity. As we scale globally and operate in increasingly fast-moving and competitive talent markets, compensation decisions must be powered by advanced analytics, market intelligence, and AI-enabled insight—not static surveys or point-in-time benchmarks.About the RoleWe’re looking for a Senior Manager, Compensation Analytics to lead complex compensation analyses and deliver high-impact insights that support hiring, promotions, retention, and equity decisions. This role focuses on building and operating advanced analytical frameworks, partnering closely with Compensation, HRBPs, Recruiting, and Finance to ensure decisions are well-informed, explainable, and practical. This is a senior individual contributor role and first of its kind. You will play a critical role in shaping how compensation data is modeled, interpreted, and applied across the People ecosystem. This role reports to our Head of Compensation & Total Rewards.Your Responsibilities:Lead the development and maintenance of compensation analytics, including market pricing, internal equity analysis, and performance-informed pay insights.Translate complex or incomplete data into clear, decision-ready recommendations for Compensation leaders, HRBPs, and recruiting partners.Partner with cross-functional teams (Recruiting, People Analytics, Equity, Finance) to support hiring, promotion, and retention decisions.Apply advanced analytical methods — including modeling, scenario analysis, and structured assumptions — to address gaps in market data or emerging roles.Identify opportunities to improve compensation workflows, tools, and reporting, balancing analytical rigor with speed and usability.Contribute to the responsible use of AI and automation in compensation analysis, with appropriate guardrails and explainability.Coach and review the work of more junior analysts as needed; may directly manage 1–2 ICs depending on team structure.We're Seeking:6-10 years of experience in compensation analytics, people analytics, finance, or a related quantitative field.Strong hands-on experience with market pricing, internal equity analysis, and pay decision support.Comfort operating in ambiguous environments with incomplete or shifting data.Proven ability to partner cross-functionally and influence decisions without owning final authority.Clear communicator who can explain analytical findings to non-technical stakeholders.Familiarity with global compensation concepts and the limitations of traditional benchmarking data.Workplace & LocationThis role can be based in our San Francisco office or remotely in the US. When applying, let us know which location(s) work for you. We also offer relocation support to new hires.If you're joining us in person, we offer relocation support and follow a hybrid schedule: three days a week in the office, with the option to work from home on Thursdays and Fridays. Our offices are set up for focus and connection—with adjustable desks, phone booths, conference rooms, stocked kitchens, and cozy spots to unwind or catch up with teammates.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disabilit ... (truncated, view full listing at source)
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