About the role:

The People Intelligence Intern will join the Centre of People Intelligence (COPI), a cross-functional capability focused on delivering decision-grade people insights to build and sustain a high-performing organisation at Chainlink Labs. COPI transforms employee communication metadata, behavioural signals, sentiment data, and people systems data into predictive insights that enable earlier and more effective talent decisions.

This internship offers a unique opportunity to work at the intersection of behavioural science, advanced analytics, and AI, contributing directly to predictive modelling efforts related to burnout, collaboration, performance, and attrition.

Responsibilities:

📍Leverage statistical analysis and predictive modelling to generate insights on key talent themes such as work-life integration, retention, organisational health, and collaboration. 📍Support the development and refinement of data-driven models that help identify emerging people trends and inform proactive talent decisions. 📍Analyze behavioral, engagement, and workforce data to surface patterns and opportunities that improve team effectiveness and overall organisational performance. 📍Analyse employee communication metadata, sentiment signals, and survey data to surface early-warning indicators. 📍Translate business questions into testable hypotheses and apply rigorous research methods to validate findings. 📍Partner with People Team stakeholders to present clear, defensible, and actionable insights. 📍Maintain high standards of documentation, methodological rigor, and data integrity when handling sensitive information.

Requirements:

📍Strong foundation in statistical modelling and research methods. 📍Experience with experimental design, hypothesis testing, and applied AI techniques. 📍Proficiency in Python, R, or similar statistical analysis tools. 📍Ability to clean, structure, and analyse complex datasets, including survey and behavioural data. 📍Demonstrated capability to translate analytical findings into clear business insights. 📍High discretion and integrity when handling sensitive employee data.

Nice-to-have: 📍Academic background in Organisational Behaviour, Organisational Psychology, Talent Management, Business Intelligence, or related fields. 📍Exposure to People Analytics methodologies and frameworks. 📍Experience analysing employee lifecycle, engagement, or performance data. 📍Familiarity with HRIS or ATS systems. 📍Prior internship or research experience in analytics, consulting, behavioural science, or HR functions. 📍Interest in predictive modelling, Organisational Network Analysis (ONA), and behavioural signal detection.

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