Why This Job is Featured on The SaaS Jobs
This Economist role sits at a growing intersection in SaaS: AI-native products that reshape how software is built, adopted, and governed. Rather than focusing on a single application area, the remit is to study real-world economic effects of AI using large datasets, which is increasingly relevant as SaaS companies embed generative AI into workflows and pricing, and face scrutiny from customers and regulators.
For a SaaS career, the long-term value is the combination of rigorous measurement and practical translation. Producing empirical work that can inform product and policy decisions builds a rare skill set in the ecosystem: connecting adoption patterns, labor market shifts, and firm behavior to decisions that affect go-to-market, platform strategy, and responsible deployment. Experience with causal inference, large-scale data, and cross-functional interpretation is broadly portable across data science, product analytics, research, and strategy functions in AI-driven SaaS.
This role is best suited to an early-career PhD economist who prefers owning end-to-end research projects and is comfortable working with technical stakeholders. It will fit someone motivated by methodological depth, careful communication of findings, and problem selection that spans multiple domains rather than a narrow, single-metric mandate.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
About the Team
Our economics team is continuously working to improve our understanding of an AI-driven economy.
About the Role
We are seeking a highly technical Economist to join the OpenAI Economic Research team studying the real-world economic impacts of AI.
This role is designed for economists with up to 5 years of professional experience post-Ph.D. who are interested in using novel, large-scale datasets to study how AI is reshaping economic systems. We are looking for candidates with deep expertise in at least one core domain relevant to AI’s economic impact, and an interest in contributing to a broader research agenda spanning labor markets, firm behavior, market dynamics, and macroeconomic change. This is an individual contributor role where the candidate will organize and execute on their own data-oriented projects.
You will work at the intersection of economic research, data science, and public policy to produce rigorous empirical work that informs decision-makers across the public, industry, and government.
Research Areas of Interest
We are particularly interested in candidates with demonstrated expertise in one or more of the following areas:
Economic Measurement of AI Impact (e.g., adoption trajectories, labor market transitions, productivity growth, and forecasting/scenario modeling for AI-driven economic change)
Macroeconomic Implications of AI (e.g., productivity, technology diffusion, economic growth)
AI and the Labor Market (e.g., employment, wages, job search, task-level impacts, skill acquisition)
Applicants are not expected to have experience across all domains. We aim to build a team with complementary strengths across these areas.
In this role, you will:
Design and execute empirical research using large-scale observational or experimental data.
Apply causal inference and/or structural modeling techniques to study AI-driven economic change.
Collaborate with cross-functional teams to translate research questions into testable frameworks and applicable takeaways across policy, product, and our organization.
Produce policy-relevant outputs, including academic papers, technical reports, and briefings.
Contribute to the development of new measurement approaches for AI’s economic impact.
Use AI across your responsibilities to scale your research impact.
You might thrive in this role if you have:
A PhD in Economics or a related quantitative field.
3–5 years of relevant work experience (industry or policy research).
Strong background in econometrics and applied microeconomics
Demonstrated experience working with large or complex datasets, with demonstrated proficiency in SQL.
Proficiency in statistical programming (e.g., Python, R).
Research related to labor economics, industrial organization, macroeconomics, or technological change.
Experience working with platform, labor market, or firm-level data.
Familiarity with causal inference, machine learning methods, or structural modeling.
About OpenAI
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.
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, disability, genetic information, or other applicable legally protected characteristic.
For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
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