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present of AI is seeking a data leader to own the warehouse, transformation layers and reporting tools while also doing hands-on analysis. The role starts solo with a remit to hire and grow the team over time.
A strong candidate has led data or analytics at a startup or scale-up, can question engineers on technical choices, and can sit with department leads to find the real question behind a request. Everyday AI use and data-driven decision making will be central.
The first data leader at a fast growing company, owning the warehouse, transformation layers and reporting tools while also doing hands on analysis. A strong candidate has led data or analytics at a startup or scale up, can question engineers on technical choices, and can sit with department leads to find the real question behind a request. The role starts solo with a remit to hire and grow the team over time.
AI shifts part of the work toward making data clean and structured enough for AI tools to use reliably, and toward judging which AI generated analysis is worth trusting. The human core stays the same: agreeing on shared metric definitions, understanding what a team actually needs, and explaining findings in plain language. The role also carries a clear brief to keep AI output useful rather than a flood of low quality reports.
The job sits inside a company whose product is a conversational AI interviewer, so the data work feeds directly into AI driven research. A candidate would gain practice shaping data so AI tools can consume it and setting standards for when AI analysis is good enough to act on. Everyday use of AI in the work itself is expected, which builds judgment about where it helps and where it does not.
This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.
Automated qualitative research platform using conversational AI agents to conduct video and voice user interviews at scale, per the company.