People Intelligence Intern

Job Description

People Intelligence Intern | Chainlink Labs

The Tone:
This is a full-time remote internship at Chainlink Labs, a company that provides the industry-standard oracle platform, bringing capital markets onchain and powering decentralized finance. The company’s infrastructure supports advanced blockchain use cases for institutional assets, lending, and payments, securing tens of trillions in transaction value. This role is crucial for developing decision-grade people insights, transforming various data points into predictive intelligence to build and sustain a high-performing organization.

The TL;DR
• Role: Internship
• Type: Full-time
• Location: Remote

• Team: Centre of People Intelligence (COPI), a cross-functional capability
• Mission: Transform employee data into predictive insights that enable earlier and more effective talent decisions.
• Tech Stack: Python, R

What You’ll Actually Do
• Insights: Generate insights on key talent themes such as work-life integration, retention, organizational health, and collaboration using statistical analysis and predictive modeling.
• Models: Support the development and refinement of data-driven models that identify emerging people trends and inform proactive talent decisions.
• Analysis: Analyze behavioral, engagement, and workforce data to uncover patterns and opportunities that enhance team effectiveness and overall organizational performance.
• Indicators: Analyze employee communication metadata, sentiment signals, and survey data to surface early-warning indicators related to organizational health.
• Research: Translate business questions into testable hypotheses and apply rigorous research methods to validate findings.

The Must-Haves
• Background: Early Career professional with a strong foundation in statistical modeling and research methods, ideally with an academic background in Organizational Behavior, Organizational Psychology, Talent Management, Business Intelligence, or related fields.
• Experience: Experience with experimental design, hypothesis testing, and applied AI techniques, including the ability to clean, structure, and analyze complex datasets such as survey and behavioral data.
• Skills: Proficiency in Python, R, or similar statistical analysis tools; demonstrated capability to translate analytical findings into clear business insights; high discretion and integrity when handling sensitive employee data.
• Bonus: Exposure to People Analytics methodologies and frameworks; experience analyzing employee lifecycle, engagement, or performance data; familiarity with HRIS or ATS systems; interest in predictive modeling, Organizational Network Analysis (ONA), and behavioral signal detection.