Data Analyst

A Data Analyst on an engineering team typically turns product and usage data into clear answers for the people building the software. A strong candidate brings solid SQL and spreadsheet skills, some scripting for cleaning and analysis, and the habit of checking numbers before trusting them. For a platform that runs many customer interviews at once, comfort with messy text and voice data and with measuring how well summaries hold up would matter.

AI tools now draft queries, charts and first-pass summaries quickly, so the analyst's time shifts toward framing the right question and judging whether the output is sound. The human parts remain deciding what counts as a good result, spotting bias in interview data, and explaining findings plainly to engineers and product people.

Working here would build hands‑on experience evaluating AI-generated summaries against source interviews and building measures of quality. That can be grown by practising on public interview or survey datasets, comparing model output to human labels, and learning basic evaluation and data quality checks.

• Data cleaning
• Python or R basics
• Careful with numbers

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.

An AI-moderated research platform that, the company says, runs and summarises hundreds of customer interviews at once, by voice, video or text.