People Intelligence Intern

Job Description

People Intelligence Intern | Chainlink Labs

The Tone:
This is a full-time internship at Chainlink Labs, located remotely. Chainlink is the industry-standard oracle platform, powering decentralized finance and bringing capital markets onchain for advanced blockchain use cases. This role is crucial for the Centre of People Intelligence (COPI), which generates decision-grade people insights to build and sustain a high-performing organization within the company. The intern will directly contribute to predictive modeling efforts that influence key talent decisions and improve organizational health.

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

• Team: Centre of People Intelligence (COPI), a cross-functional capability
• Mission: Transform employee communication, behavioral signals, sentiment, and people systems data into predictive insights for effective talent decisions.
• Tech Stack: Python, R, or similar statistical analysis tools

What You’ll Actually Do
• Analyze data for talent insights: Generate insights on work-life integration, retention, organizational health, and collaboration using statistical analysis and predictive modeling.
• Develop and refine predictive models: Support the creation and improvement of data-driven models to identify emerging people trends and inform proactive talent strategies.
• Interpret data for team effectiveness: Analyze behavioral, engagement, and workforce data to surface patterns and opportunities that enhance team and overall organizational performance.
• Detect early-warning indicators: Analyze employee communication metadata, sentiment signals, and survey data to identify potential issues early.
• Formulate hypotheses and validate findings: Translate business questions into testable hypotheses and apply rigorous research methods to confirm discoveries.

The Must-Haves
• Background: Strong foundation in statistical modeling and research methods.
• Experience: Experience with experimental design, hypothesis testing, and applied AI techniques, along with the ability to clean, structure, and analyze complex datasets.
• Skills: Proficiency in Python, R, or similar statistical analysis tools, demonstrated capability to translate analytical findings into clear business insights, and high discretion with sensitive employee data.
• Bonus: Academic background in Organisational Behaviour, Organisational Psychology, Talent Management, Business Intelligence, or related fields; exposure to People Analytics methodologies; experience analyzing employee lifecycle, engagement, or performance data; familiarity with HRIS or ATS systems; prior internship/research in analytics, consulting, behavioural science, or HR; interest in predictive modeling, Organisational Network Analysis (ONA), and behavioural signal detection.