Why This Job is Featured on The SaaS Jobs
People Data Scientist roles are becoming a defining capability in modern SaaS, where product velocity and headcount scale can quickly outpace the rigor of internal decision-making. This position stands out because it applies research science and experimentation to People programs, bringing the same measurement discipline often used in product analytics into the operating system of a tech organization. The hybrid San Francisco setup also signals proximity to leadership and cross-functional partners, which matters for influence-heavy analytics work.
For a SaaS career, the durable value here is learning how to turn ambiguous organizational questions into governed datasets, repeatable research designs, and decision-ready narratives. Experience with fairness and validation work, evaluation of AI-assisted workflows, and privacy-preserving analytical pipelines maps well to the broader SaaS shift toward automation, compliance expectations, and evidence-based operations. The emphasis on building playbooks and self-service tooling is also a strong proxy for developing scalable internal data products, a transferable skill across growth-stage and enterprise SaaS environments.
This role fits professionals who prefer careful methodology over ad hoc reporting and who are comfortable partnering across People, engineering, and systems teams. It will suit someone motivated by high-stakes measurement problems, clear documentation standards, and communicating tradeoffs to senior stakeholders in a technical organization.
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 Role
As a People Data Scientist, you will bring deep expertise in research science, measurement, and experimentation to OpenAI’s most important People programs. You will design studies, evaluate people processes, build research frameworks, and help leaders understand how we can better empower employees, strengthen organizational systems, and deliver exceptional employee experiences.
We’re looking for an experienced data scientist who can translate ambiguous People questions into rigorous research designs, validated insights, and actionable recommendations.
This role will be based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.
In this role you will:
Design rigorous research and evaluation strategies for organizational health, manager effectiveness, employee experience, and talent outcomes.
Conduct fairness, adverse impact, validity, reliability, calibration, and measurement-invariance analyses for high-stakes People processes and AI-assisted workflows.
Apply advanced statistical modeling, machine learning, and research methods to inform program design, evaluate effectiveness, and quantify business impact.
Partner with People Operations, data engineering, and people systems teams to define data requirements, improve data quality, establish documentation standards, and ensure research datasets are governed, reproducible, and privacy-preserving.
Build scalable people science infrastructure, including self-service agentic tools, automated validation workflows, reusable research datasets and analytical pipelines.
Develop research playbooks that establish rigorous standards for study design, measurement, validation, and documentation, enabling high-quality, repeatable, and scalable research across the organization.
Communicate findings through concise, executive-ready narratives.
You might thrive in this role if you:
Deep curiosity, strong attention to detail, and passion for solving ambiguous and complex problems with creativity.
Exceptional strength in research design, experimentation, measurement, causal inference, and statistical modeling, including hands-on experience with psychometrics, survey methodology, structural equation modeling, multilevel modeling, randomized controlled experiments, A/B testing, quasi-experimental design, validation studies, and machine learning evaluation.
High proficiency in R or Python and SQL, with experience working across complex, messy datasets.
Experience building measurement systems, research programs, data products, reusable analytics frameworks, self-service tools, and governed analytical workflows.
Ability to communicate complex methods and tradeoffs clearly to senior leaders, technical partners, and non-technical audiences.
Preferred qualifications
Experience evaluating AI-assisted workflows, algorithmic systems, and human-AI decision processes in operational contexts, including familiarity with model evaluation methods.
Advanced degree in Industrial-Organizational Psychology, Organizational Behavior, Quantitative Psychology, Behavioral Economics, Statistics, Economics, Data Science, or a related field; PhD preferred.
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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