Humans are unreliable narrators of their own behavior. Memory fails, incentives distort answers, and social pressure warps what people say away from what they actually do. Backed by General Catalyst, Felicis and Redpoint.
About the role
As a Prediction Researcher, you will own difficult, open questions about aggregate human behavior and future outcomes. You will formulate hypotheses, construct or curate datasets, build predictive methods, design evaluations, inspect failures, and communicate what the evidence supports—including when a result is null, unstable, or less useful than a simple baseline.
More about this role
Aaru builds simulations of human behavior. Each simulation contains a population of AI agents, each representing a person who could plausibly exist in the real world and capable of making decisions within a modeled environment. Companies and institutions use these simulations to test consequential choices before committing—from product launches and pricing decisions to strategic communications and policy changes.
Building a useful simulation requires more than generating plausible text. Populations must represent real people and groups; predictions must be calibrated; simulations must remain coherent as conditions change; and the product must make the resulting evidence legible enough to support real decisions.
We are a small, in-person team in New York. We work with urgency, high ownership, and intellectual honesty. We expect people to surface inconvenient evidence, change their minds quickly, and carry important work all the way to a result.
Prediction Research builds systems that estimate future or otherwise unknown outcomes from data. The team's primary object is the population-level outcome: given a population, a question, and the relevant context, what aggregate result...
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