OpenAI13 дней назад

People Research Scientist

Зарплата не указана

РЫНОК

16 250 ₽медиана по профессии

Data Scientist · 212 вакансий с указанной зарплатой

5 000половина предложений: 13 084–21 768120 000

Работодатель не указал зарплату — сравните с рынком сами.

Полная занятостьSan Francisco

Обязанности

01Design rigorous research and evaluation strategies for recruiting, organizational health, manager effectiveness, employee experience, and talent outcomes
02Apply advanced statistical modeling, machine learning, and research methods to inform program design, evaluate effectiveness, and quantify business impact
03Partner 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
04Build scalable people science infrastructure, including self-service agentic tools, automated validation workflows, reusable research datasets and analytical pipelines
05Develop research playbooks that establish rigorous standards for study design, measurement, validation, and documentation, enabling high-quality, repeatable, and scalable research across the organization
06Communicate findings through concise, executive-ready narratives

01Deep curiosity, strong attention to detail, and passion for solving ambiguous and complex problems with creativity
02Exceptional 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
03High proficiency in R or Python and SQL, with experience working across complex, messy datasets
04Experience building measurement systems, research programs, data products, reusable analytics frameworks, self-service tools, and governed analytical workflows
05Ability to communicate complex methods and tradeoffs clearly to senior leaders, technical partners, and non-technical audiences
06Sound judgment in handling sensitive employee data, including privacy, fairness, bias, and responsible research practices