WIRE SALAD OÜ

Data Analyst

• You'll build the data function that keeps up.
• Build the data backbone: pipelines in Airbyte, models in BigQuery, dashboards in Looker, experiments in Statsig.
• Clean inputs, consistent definitions, documented logic - the foundation everything else runs on.
• Own the metrics that matter: LTV:CAC, ROAS, LTV, retention, funnel conversion, payback periods, channel attribution.
• Define them once, get everyone aligned, and put an end to "wait, which number is right?"
• Go proactive, not reactive: don't wait for someone to ask what's broken - build AI-assisted anomaly detection that flags it first.
• Spot the channel quietly leaking spend at 3am. Catch the cohort converting 40% better and explain why.
• Democratise the data: not every question should land in your inbox. Build self-serve dashboards people actually use, write docs people actually read, and raise data literacy across the company.
• Use AI like it's 2026, because it is: if a tool makes you 10x faster or sharper, we want you using it - and teaching the rest of us.
• Raise the bar: question inconsistencies, chase down edge cases, document what you build, and hold everyone (including yourself) to a high standard of accuracy.