Product Analyst

Tango Me

Що робити

Ownership. Be the analytics counterpart for a product domain 1:1 chat, content packs, negotiations, live streaming — you become the person PMs and engineers come to for any number in that area, and the person accountable when it’s wrong.
Pipelines. Build and maintain the datasets behind your domain. Write production transformations as SQL and YAML pipeline config, with freshness, uniqueness and validity checks. Your work goes through code review like any engineer’s.
Events. Specify instrumentation before it’s built. Write the BI event spec for new features across Android, iOS and Web; then verify after release that events actually fire the way the spec said, and chase the gaps when they don’t.
Dashboards. Own dashboards and the models under them. Including retiring the ones nobody opens. A dashboard with no reader is a cost, not an asset.
Analysis. Investigate what moved and why Revenue and conversion anomalies, feature performance, behavioural questions from PMs. Present findings to people who will act on them.

Advanced SQL, including window functions and multi-source joins — and the ability to reason about what a query costs, not only whether it returns.
A strong experimentation background. Hypothesis testing, confidence intervals, power and minimum detectable effect — and the failure modes: peeking at a running test, multiple comparisons, hunting for a segment where the result works. You should also be the kind of person who checks that the experiment itself is sound before trusting its numbers.
3+ years as a product or data analyst on consumer products, with real exposure to both mobile and web.
Critical use of AI analytics tooling. We use an internal Claude-based layer over BigQuery heavily. We want someone who checks what it produces before passing it on.
Comfort shipping code: git, merge requests, reading and reviewing someone else’s SQL. You’ll write production pipeline code, not only notebooks and queries.

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