Build AI-native intelligence systems behind Replit's hiring, comp, and workforce decisions

Replit is hiring a Data Scientist, People to move beyond dashboards and build predictive models and AI agents that directly recommend compensation adjustments, flag attrition risk, and inform hiring and org-design decisions. The role requires strong SQL/Python, causal inference and experimentation depth, and hands-on use of LLMs on unstructured People data (exit interviews, performance reviews). Expect the interview to test statistical rigor, applied AI-agent design for high-stakes decisions, and comfort handling sensitive compensation/org data.

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What this interview tests

Compensation and workforce predictive modeling (attrition risk, offer competitiveness)
Statistical rigor: experimentation design and causal inference
Designing AI agents for high-stakes People decisions with human review
Applying LLMs to unstructured People data (exit interviews, performance reviews)
Organizational effectiveness analysis (spans, layers, talent density)
Handling sensitive compensation/org data with discretion; executive communication