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Analytics Engineer, People

Anthropic LogoAnthropic
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Salary

$220,000 - $275,000

Location

San Francisco, CA | Seattle, WA. Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time.

Anthropic is seeking an Analytics Engineer (People) to build data infrastructure and analytics solutions that provide strategic insights into workforce trends and employee experience. As a self-starter in this individual contributor role, you'll work with executives and cross-functional teams to develop data-driven strategies that enhance organizational effectiveness. The position involves building data pipelines, designing architecture, and creating analytics solutions while maintaining high-quality output in a fast-paced environment. You'll be pushing the boundaries of AI-powered people analytics as Anthropic works toward its mission of building safe and beneficial AI systems.

Responsibilities

Data Infrastructure & Engineering

  • Design and develop scalable data pipelines and ETL/ELT processes for people analytics data
  • Build and maintain robust data models and dimensional schemas to enable efficient reporting and analysis
  • Ensure data quality, consistency, and governance across all people analytics data
  • Implement and maintain version control and software engineering best practices for analytics projects
  • Develop and maintain APIs and integrations with various HR systems and data sources

Data Modeling & Analysis

  • Develop and implement data models and algorithms to analyze workforce trends and provide actionable insights
  • Conduct deep-dive analyses to uncover trends, patterns, and correlations within employee data
  • Apply advanced statistical methods including survival models, regression analyses, and predictive modeling to solve people-related challenges
  • Present findings to senior leaders with clear recommendations for improvements
  • Manage urgent analytics requests with quick turnaround times

Visualization & Communication

  • Create and maintain interactive dashboards and visualizations that help communicate complex data insights to key stakeholders
  • 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 executives to understand business challenges and translate them into technical solutions
  • Advise on best practices for integrating and analyzing data from various HR systems (e.g., Workday, ATS, surveys) and external sources
  • Take ownership of diverse responsibilities from research projects to operational process implementation, root cause analysis, and program management

You might be a good fit if you:

  • Have 5+ years of experience in analytics engineering, data engineering, or data science, with proficiency in SQL and Python, and solid experience in data pipeline development and ETL/ELT processes
  • Have experience with data warehousing concepts, dimensional modeling, data architecture, and version control systems (Git)
  • Are skilled in data visualization tools like Looker or Hex, and comfortable with data modeling frameworks like dbt
  • Have experience with API development and integration
  • Demonstrate strong understanding of HR data, employee lifecycle processes, and key talent management metrics
  • Have experience working with large-scale HR data and integrating datasets from multiple systems (HRIS, ATS, surveys)
  • Are comfortable with advanced statistical techniques including regression analysis, predictive modeling, and survival analysis
  • Can manage multiple projects and deliver insights in a fast-paced environment, with a can-do attitude and ability to work in rapid-response situations
  • Are AI-first and AI-forward, eager to learn new concepts and explore bleeding-edge solutions in people analytics
  • Are a team player who maintains collegiality and can effectively collaborate across different teams
  • Hold a degree in a quantitative field (e.g., Statistics, Mathematics, Economics, Computer Science, Data Science) or related disciplines

Strong candidates may also have:

  • Familiarity with cloud-based data platforms (e.g., AWS, GCP, Databricks, Snowflake)
  • Experience working with AI/ML models in a people analytics context to drive predictive insights
  • Experience with employee listening and user research methodologies
  • Understanding of data governance principles and regulatory compliance (e.g., GDPR, data privacy)
  • Experience in managing cross-functional projects with both technical and non-technical stakeholders
  • Track record of implementing automation and AI-powered solutions to streamline people analytics processes
  • Experience with agile methodologies and working in sprint cycles

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