Recruiting Data Engineering & Analytics
San Francisco, CA | Seattle, WAFull-TimeMid-levelTalent / HR
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.
About the Role
- This role sits at the intersection of data engineering and recruiting analytics. You'll build the technical foundation that powers insights about hiring, engagement, performance, and workforce planning while working with a team that's actively experimenting with AI to transform how we understand and support our workforce.
- As a key member of our data-driven culture, you'll design scalable data architectures, optimize our analytics infrastructure, and transform raw recruiting data into trusted, reusable datasets. But you'll also need to be scrappy—sometimes the right solution is a well-crafted Google Sheet or a quick prototype, not a fully engineered pipeline. We value creativity and pragmatism alongside technical excellence.
- This role offers the opportunity to make a significant impact on how we attract, develop, and retain the exceptional talent needed to advance AI safety.
Data Infrastructure & Modeling
- Refactor and optimize our existing BigQuery tables to create a scalable data foundation that supports traditional BI tools (like Looker) and enables AI-driven insights across the company
- Design scalable data architectures and build dimensional models that transform raw recruiting data into trusted, reusable datasets for self-serve analytics while maintaining performance
- Model downstream tables for custom reporting and analytics
- Implement data governance including documentation, lineage tracking, quality monitoring, and proactive alerting systems
- Develop and maintain automated reporting solutions that scale with organizational growth
Data Analysis & Insights
- Analyze complex datasets to identify trends, patterns, and opportunities across the employee lifecycle
- Conduct rigorous statistical analysis to support evidence-based decision-making for talent management initiatives
- Perform root cause analysis on people-related metrics to understand underlying drivers of organizational outcomes
- Design and execute research projects that advance our understanding of what drives employee success and satisfaction
Visualization & Communication
- Create and maintain interactive dashboards and visualizations that help communicate complex data insights to key stakeholders
- Come up with creative solutions to displaying data—whether that's a polished Looker dashboard, a quick Google Sheets prototype, or leveraging AI for novel approaches
- Translate complex data analyses into clear, compelling narratives for both technical and non-technical audiences
- Convert insights into actionable recommendations and drive implementation of solutions
- Collaborate with company leaders to identify, track, and iterate key performance indicators (KPIs) for talent management
Cross-Functional Partnerships
- Partner with stakeholders to define and scope people analytics projects that align with organizational goals
- Work directly with recruiting leaders, hiring managers, and executives to understand business challenges and translate them into technical solutions
- Advise on best practices for integrating and analyzing data from various HR systems and external sources
- Take ownership of diverse responsibilities from research projects to operational process implementation, root cause analysis, and program management
You May Be a Good Fit If You
- Have 5+ years in data engineering or analytics engineering, preferably with experience in recruiting analytics, people analytics, or related fields
- Are an expert in BigQuery including optimization, partitioning, and performance tuning
- Have built dimensional models and understand slowly changing dimensions
- Are proficient in SQL, Python, and modern tools like dbt and Fivetran
- Have experience with data visualization tools (Tableau, Looker, Looker Studio, Power BI)
- Have implemented data security and privacy controls in cloud warehouses
- Are comfortable working with messy or incomplete data
- Possess excellent communication skills and can translate complex analytical findings into actionable business insights
- Are creative and scrappy—you know when to build a robust data pipeline and when a Google Sheet with some clever formulas will get the job done faster
- Are results-oriented with a bias towards flexibility and impact over perfection
- Thrive in a fast-paced, collaborative environment and enjoy working closely with cross-functional teams
- Care about ensuring that advanced AI systems are developed safely and are passionate about our mission
Strong Candidates May Also Have
- Advanced degree in Statistics, Data Science, Computer Science, or related quantitative field
- Familiarity with ATS platforms (Greenhouse, Lever) and their data structures
- Experience building data pipelines for survey data and text analytics
- Background in privacy-enhancing technologies or sensitive data handling
- Experience with A/B testing and experimental design
- Previous experience in high-growth technology companies, startups, or AI/ML organizations
- Familiarity with data privacy regulations and ethical considerations in people analytics
- Familiarity with workforce planning and predictive analytics use cases
Representative Projects
- Building and optimizing BigQuery data models to enable self-serve analytics for recruiting teams and hiring managers
- Modeling data and building dashboards to drive better decision making around interviewer training and deeper understanding of interviewer capacity and constraints
- Implementing data governance and quality monitoring systems for sensitive employee data
- Spinning up a quick Google Sheets tracker to unblock a time-sensitive hiring initiative while the long-term solution is in development
- Conducting research on the effectiveness of our hiring processes and recommending improvements to reduce bias and improve candidate experience
- Collaborating with our compensation team to develop data-driven compensation analysis to ensure pay equity and market competitiveness
- Working with recruiting leaders to help them report to the business on basic recruiting metrics, hiring predictions, and opportunities for improvement
- 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.
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.
