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Analytics Engineer, People

San Francisco, CA | Seattle, WA

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.

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

Deadline to apply: None. Applications will be reviewed on a rolling basis. 

The expected salary range for this position is:

Annual Salary:

$220,000 - $275,000 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.

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