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YubHub-native raw fields carry `x-` prefix.","jobs":[{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_ba891bfc-12f"},"title":"Applied Data Scientist, Unit Economics Understanding","description":"<p><strong>Applied Data Scientist, Unit Economics Understanding</strong></p>\n<p><strong>Location</strong></p>\n<p>San Francisco</p>\n<p><strong>Employment Type</strong></p>\n<p>Full time</p>\n<p><strong>Department</strong></p>\n<p>Strategic Finance</p>\n<p><strong>Compensation</strong></p>\n<ul>\n<li>$230K – $385K • Offers Equity</li>\n</ul>\n<p>The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.</p>\n<ul>\n<li>Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts</li>\n</ul>\n<ul>\n<li>Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)</li>\n</ul>\n<ul>\n<li>401(k) retirement plan with employer match</li>\n</ul>\n<ul>\n<li>Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)</li>\n</ul>\n<ul>\n<li>Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees</li>\n</ul>\n<ul>\n<li>13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)</li>\n</ul>\n<ul>\n<li>Mental health and wellness support</li>\n</ul>\n<ul>\n<li>Employer-paid basic life and disability coverage</li>\n</ul>\n<ul>\n<li>Annual learning and development stipend to fuel your professional growth</li>\n</ul>\n<ul>\n<li>Daily meals in our offices, and meal delivery credits as eligible</li>\n</ul>\n<ul>\n<li>Relocation support for eligible employees</li>\n</ul>\n<ul>\n<li>Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.</li>\n</ul>\n<p>More details about our benefits are available to candidates during the hiring process.</p>\n<p>This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.</p>\n<p><strong>About the Role</strong> This role focuses on building the strategic unit economics understanding of OpenAI, guiding sustainable growth to make it the most impactful company of our generation and beyond.</p>\n<p>You will lead the development of foundational causal inference and data science models and frameworks to predict and quantify the drivers of customer lifetime value (LTV), translating deep data insights into strategic decisions and growth levers. The role requires both technical depth and executive-level communication.</p>\n<p>This position is based in our San Francisco HQ with a hybrid work model (three days in office per week). Relocation assistance is available.</p>\n<p><strong>The Vision</strong></p>\n<ul>\n<li>Build causal inference and predictive analytics capabilities to measure and forecast LTV across customer segments (B2C and B2B), and quantify the incremental impact of different actions or product features on customer LTV.</li>\n</ul>\n<ul>\n<li>Design customer “happy paths” by identifying adoption journeys that maximize lifetime value while ensuring customers gain the most from our ecosystem.</li>\n</ul>\n<ul>\n<li>Analyze price elasticity to guide product packaging, monetization, and pricing strategies.</li>\n</ul>\n<p><strong>In this role, you will:</strong></p>\n<ul>\n<li>Partner with cross-functional teams (Finance, Product, Data Engineering, GTM, and other DS teams) to build causal inference and predictive models that drive business decisions.</li>\n</ul>\n<ul>\n<li>Develop and maintain LTV models across product lines and customer cohorts.</li>\n</ul>\n<ul>\n<li>Architect scalable frameworks and models that democratize economic insights for leadership and functional teams.</li>\n</ul>\n<ul>\n<li>Support strategic pricing and investment decisions with robust analytical and causal evidence.</li>\n</ul>\n<ul>\n<li>Lead cross-functional data science initiatives, ensuring analytical rigor, clarity, and timely delivery.</li>\n</ul>\n<p><strong>You might thrive in this role if you:</strong></p>\n<ul>\n<li>Executive communication — ability to distill complex analysis into clear, actionable recommendations for leadership.</li>\n</ul>\n<ul>\n<li>Technical breadth — comfort spanning ROI analysis, causal inference, statistical modeling, and ML predictive models; strong experience with Python and SQL.</li>\n</ul>\n<ul>\n<li>Strategic judgment — ability to connect analytical insights to business impact, delivering the “so what” that informs leadership decisions.</li>\n</ul>\n<ul>\n<li>Collaboration and ownership — thrive in a fast-paced, cross-functional environment and proactively take projects from concept to delivery.</li>\n</ul>\n<p><strong>Qualifications</strong></p>\n<ul>\n<li>MS or PhD in a quantitative field (Statistics, Economics, Applied Math, Operations Research, Computer Science, etc.).</li>\n</ul>\n<ul>\n<li>7+ years of experience in applied data science, causal inference, or quantitative strategy.</li>\n</ul>\n<ul>\n<li>Proven record of delivering high-impact insights to executive leadership.</li>\n</ul>\n<ul>\n<li>Experience building scalable analytical frameworks and models that inform business decision-making.</li>\n</ul>\n<p><strong>About OpenAI</strong></p>\n<p>OpenAI 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.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_ba891bfc-12f","directApply":true,"hiringOrganization":{"@type":"Organization","name":"OpenAI","sameAs":"https://jobs.ashbyhq.com","logo":"https://logos.yubhub.co/openai.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/openai/9f69106f-c2c9-4f14-9938-f38eb42cab50","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$230K – $385K • Offers Equity","x-skills-required":["Python","SQL","Causal Inference","Statistical Modeling","ML Predictive Models","Data Science","Data Engineering","GTM","Finance","Product"],"x-skills-preferred":["Executive Communication","Technical Breadth","Strategic Judgment","Collaboration and Ownership"],"datePosted":"2026-03-06T18:34:05.485Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, SQL, Causal Inference, Statistical Modeling, ML Predictive Models, Data Science, Data Engineering, GTM, Finance, Product, Executive Communication, Technical Breadth, Strategic Judgment, Collaboration and Ownership","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":230000,"maxValue":385000,"unitText":"YEAR"}}}]}