Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Python @ 5
SQL @ 5
R @ 5
Statistics @ 3
Machine Learning @ 5
Data Science @ 3
Leadership @ 3
Communication @ 6
NLP @ 2
AI @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Anthropic is seeking a People Research Scientist to join the People Data Solutions team to advance understanding of employee experience, manager effectiveness, organizational health, and workforce dynamics. This role sits at the intersection of organizational science, behavioral research, and people strategy and involves designing rigorous studies and translating findings into evidence-based people decisions across a growing AI safety company.
Responsibilities
- Design and execute systematic research studies to answer questions about employee experience, manager effectiveness, and organizational health
- Generate and test hypotheses about people programs, employee behavior, and workforce outcomes using experimental and quasi-experimental methods
- Conduct longitudinal studies tracking employee cohorts and perform meta-analyses of people interventions
- Navigate research ethics considerations when studying employee data
- Design, analyze, and iterate on employee listening programs including engagement, pulse, and lifecycle surveys
- Apply psychometric methods to validate survey instruments and ensure measurement reliability
- Translate survey findings into strategic recommendations and present findings to senior leadership
- Conduct research on manager behaviors, competencies, and their impact on team outcomes; build measurement frameworks for manager effectiveness programs
- Study organizational dynamics including team composition and collaboration patterns and their relationship to performance outcomes
- Build compelling visualizations and dashboards; develop self-service analytics capabilities for People team partners
Requirements
- Advanced degree (Master’s or PhD) in I/O Psychology, Organizational Behavior, Statistics, Data Science, Economics, Behavioral Science, or related field (Bachelor’s required at minimum per Logistics)
- 5+ years of experience in research, people analytics, or related quantitative fields with strong research methodology expertise
- Experience with experimental design, hypothesis testing, longitudinal research methods, and causal inference
- Proficiency in SQL and Python and/or R; experience in statistical analysis and machine learning
- Experience with survey design, psychometric methods, and employee listening programs
- Experience building visualizations and dashboards and communicating findings to influence stakeholders
- Comfortable working in a People Analytics tech stack and collaborating with data engineers; ability to navigate sensitive topics diplomatically while maintaining analytical rigor
Strong candidates may also have
- Background specifically in people analytics
- Experience designing and analyzing employee engagement or pulse surveys
- Deep knowledge of manager effectiveness research and organizational science
- Experience building self-service analytics tools or dashboards
- Understanding of employee lifecycle metrics and people KPIs
- Experience in high-growth technology companies or AI/ML organizations
- Familiarity with network analysis, NLP, advanced statistical methods
- Experience with BigQuery and modern data stack tools
- Experience with Qualtrics and Workday
Logistics
- Locations: San Francisco, CA and New York City, NY (United States)
- Location-based hybrid policy: staff expected to be in an office at least 25% of the time
- Education requirements: at least a Bachelor's degree in a related field or equivalent experience
- Visa sponsorship: Anthropic states they sponsor visas and will make reasonable efforts to obtain a visa if an offer is made
Compensation
- Annual salary range: $245,000 - $310,000 USD
Benefits
- Competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and office space for collaboration
How we're different
- Anthropic emphasizes large-scale, collaborative AI research focused on reliable, interpretable, and steerable AI. The team values impact, empirical science approaches, and strong communication skills. Candidates are encouraged to apply even if they do not meet every qualification.