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About Anthropic

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 Analytics Scientist to join our People Data Solutions team, focusing on recruiting and talent acquisition research. You'll be the research expert supporting our Recruiting organization, using rigorous scientific methods to advance our understanding of how we attract and assess exceptional talent. This role sits at the intersection of recruiting science, behavioral research, and talent strategy - developing novel frameworks and conducting systematic research that drives evidence-based hiring decisions across our growing organization.

This role offers the opportunity to make a significant impact on both our talent acquisition practices and the broader field of recruiting science.

Responsibilities:

Research Design & Scientific Inquiry

Design and execute systematic research studies to answer fundamental questions about talent acquisition effectiveness
Generate and test hypotheses about recruiting processes, candidate behavior, and hiring outcomes using rigorous experimental and quasi-experimental methods
Conduct longitudinal studies tracking hiring cohorts over multiple years to understand long-term talent outcomes
Perform meta-analyses of recruiting interventions across the industry to identify best practices and knowledge gaps
Navigate research ethics considerations when studying candidate and employee data, ensuring responsible research practices

Talent Analytics & Insights

Transform data into actionable insights and recommendations for talent acquisition leadership
Develop frameworks to measure and improve hiring quality and long-term outcomes
Apply advanced analytics and experimental methods to optimize recruiting strategies

Process Optimization & Operations

Analyze and enhance end-to-end recruiting processes and team effectiveness
Design research studies to identify opportunities for process improvement
Support strategic initiatives including geographic expansion and competitive positioning

Assessment & Decision Science

Evaluate and improve candidate assessment methodologies
Build predictive models and measurement frameworks for talent decisions

You may be a good fit if you:

Hold an advanced degree (Master's or PhD) in Statistics, Data Science, I/O Psychology, Economics, Behavioral Science, or related research field
Have 5+ years of experience in research, people analytics, or related quantitative fields with demonstrated research methodology expertise
Experience with experimental design, hypothesis testing, longitudinal research methods, and causal inference
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
Experience with causal inference, experimental design, and A/B testing
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 build teams

Strong candidates may also have:

Background in recruiting analytics specifically (not just general analytics)
Experience building self-service analytics tools or dashboards
Understanding of candidate lifecycle metrics and recruiting KPIs
Previous experience in high-growth technology companies or AI/ML organizations
Familiarity with network analysis, NLP, or advanced statistical methods
Experience with BigQuery and modern data stack tools
Experience with Greenhouse or similar ATS platforms

The expected salary range for this position is:

Annual Salary:$245,000—$300,000 USD

Logistics

Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.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.

How we're different

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.

Come work with us!

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