Anthropicは、People Data Solutionsチームのピープル・リサーチ・サイエンティストを募集しています。産業組織心理学等の修士・博士号を持ち、採用分析や統計的手法に精通していることが必須です。採用ファネルの最適化、評価ツールの検証、データ駆動型の意思決定フレームワークの構築を主導します。SQLおよびPython/Rのスキルに加え、複雑な研究結果を経営層に伝える能力が求められます。
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
We are seeking a Recruiting Research Scientist to join our People Data Solutions team. You’ll be the research expert supporting our Recruiting organization, using rigorous scientific methods to advance our understanding of recruiting funnels, interview effectiveness, candidate experience, and recruiting capacity. This role sits at the intersection of organizational science, behavioral research, and people strategy – developing novel frameworks and conducting systematic research that drives evidence-based people decisions across our growing organization.
This role offers the opportunity to make a significant impact on both our recruiting practices and the broader field of people science at a leading AI safety company.
Design and execute systematic research studies to answer fundamental questions about recruiting funnel health, assessment quality, candidate experience, and quality of hire
Generate and test hypotheses about sourcing strategies, interview design, and selection decisions using rigorous experimental and quasi-experimental methods
Conduct mixed-method research to understand what are the drivers and blockers to recruiting operations.
Navigate research ethics considerations when studying candidate data, ensuring responsible research practices
Design and execute validation studies to assess the quality of interviews and other selection tools
Utilize psychometric techniques to analyze and improve interviewer calibration and rating consistency
Lead investigative research into innovative approaches for candidate assessment
Design the metrics framework for recruiting org health — defining the canonical KPIs, dimensions, and definitions that leadership uses to understand funnel performance, capacity, and hiring quality
Establish the governance and definitional rigor that keeps metrics consistent across tools and reporting surfaces
Architect analytical solutions that convert research insights into actionable products, empowering stakeholders to execute data-driven scenario and strategic planning
Quantify the adoption and downstream impact of deployed tools, driving iterative improvements
Build compelling visualizations and dashboards that make complex research findings accessible to diverse audiences
Present research findings to senior leadership with clear, actionable recommendations
Hold an advanced degree (Master’s or PhD) in I/O Psychology, Organizational Behavior, Statistics, Data Science, Economics, Behavioral Science, or a related research field
Have experience with selection research, assessment validation, psychometrics, or recruiting funnel analytics
Are comfortable working in the People Analytics tech stack and collaborating with data engineers
Are proficient in SQL and Python/R, with experience in statistical analysis and machine learning
Have experience with data visualization and can tell compelling stories with research findings
Possess excellent communication skills and can influence stakeholders at all levels
Thrive in ambiguity and can balance rigor with pragmatism
Have a track record of challenging assumptions with data and changing long-held practices
Can navigate sensitive topics diplomatically while maintaining analytical rigor
Demonstrate intellectual humility and comfort with iterative discovery
Use data to improve how organizations find, assess, and hire talent
5 + years of experience in research, people analytics, or related quantitative fields with demonstrated research methodology expertise
Background in recruiting analytics specifically (not just general analytics)
Experience running interview or assessment validation studies
Experience building self-service analytics tools or dashboards
Previous experience in high-growth technology companies or AI/ML organizations
Familiarity with network analysis, machine learning, or advanced statistical methods
Experience with BigQuery and modern data stack tools
Experience with Greenhouse, Gem, ModernLoop, or similar recruiting tools
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:
$285,000—$380,000 USD
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
