Senior Data Analyst
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 16h ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 7d ago
The date the source published, not the day we noticed it (2026-09-24). Last seen at its source just now.
We have tracked this listing since 24 Sep 2026 (7 days). The employer's own board has carried it every time we have read it, most recently just now.
Is it remote?
Berlin/Remote
That is the location the employer filed this posting under. Quoted as written — we do not re-word the source's own location.
Who may apply?
Berlin
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay $99.6k–187.6k/yr
Middle 50% of 43 listings that do state pay — Operations · all levels · EMEA · USD/year. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
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ashby employer's own board first seen 7d ago · last seen just now
The listing
Your mission
We're a small data team with a big job: helping everyone at Cosuno make better decisions. Our data platform is stable and in good hands. What we need now is someone who takes our most important, open-ended business questions and answers them properly: in depth, with little guidance, and often before anyone thought to ask.
You'll work across product and commercial topics. How do general contractors and subcontractors actually use our platform? What makes some accounts grow into company-wide rollouts? Which levers move our funnel the most? You'll work closely with Product, Sales, Customer Success and leadership, and we expect you to have opinions.
In your first few months, you might:
Work out what drives account growth: which behaviours predict long-term retention and expansion, and how Sales and Customer Success can act on them.
Map how our customers really use the product: which workflows stick, where new features find their audience, and what healthy adoption looks like in an account's first months.
Pick a question nobody has asked yet, answer it, and change a product or go-to-market decision with the result.
Build the dbt models and Looker views your analyses need, so the next person can answer the question themselves.
How we work
Questions Over Tickets: You don't wait for requests. You figure out what matters and go after it.
Depth Over Dashboards: One analysis that changes a decision beats ten reports nobody reads.
Pragmatic by Default: Simple processes, fast iterations, and the lightest method that gives a trustworthy answer.
Clarity Wins: A finding is only as good as how well others understand it and act on it.
AI-Native by Default: We work heavily with Claude Code and other AI tools and expect everyone to use them fluently.
Your profile
5+ years in analytics at fast-growing startups or scaleups, ideally B2B SaaS, where your work shaped product or commercial decisions.
An exceptional ability to reason through ambiguous business problems: framing the right question, choosing a sound approach, and landing on a clear recommendation.
Hands-on experience in both product analytics (usage, adoption, engagement, experimentation) and commercial analytics (retention, expansion, funnel, pricing).
A track record of driving your own analytical agenda with minimal guidance.
Strong SQL and professional experience with dbt and a BI tool (a strong command of Looker is a big plus). You build the models and views you need instead of waiting for them.
Solid Python for analysis and scripting.
Strong, hands-on familiarity with AI tools, especially Claude Code, and a habit of using them in your daily work.
Excellent written and spoken English. You can explain a complex finding in one clear paragraph.
Bonus
Experience with marketplaces or two-sided platforms.
Experience in vertical SaaS, construction tech or procurement.
Experience with BigQuery.