What a Data Analyst does on a data science team.

Skills and scope are agreed before delivery starts, so the first sprint is productive rather than a ramp-up month. The work runs to the same backlog, the same repositories and the same definition of done as your own team's.

Data Analyst skills and technology we assign for

  • Ad hoc analysis against business questions, with the caveats stated rather than buried.

  • Building and maintaining dashboards people actually open more than once.

  • Defining and documenting metrics so numbers stop being argued about in meetings.

  • Automating recurring reports so the same query is not rerun manually every Monday.

  • Investigating data quality issues found during analysis and raising them upstream.

Seniority levels we assign.

Junior to mid. This role rewards business understanding and SQL fluency over advanced statistics. Seniority is one of the inputs in how the monthly fee is built.

When a Data Analyst is the right assignment.

Often the fastest route to value where a warehouse exists but is underused. On an ongoing roadmap this role is most often assigned alongside a Data Scientist or a BI Developer. All 4 roles in this service line can sit on the same agreement, and capacity moves between them at the monthly cycle rather than requiring a new contract. At Azendo this sits inside data science, on the same agreement as the rest of the team.

160 h
Typical monthly capacity for this role
Fixed
Monthly price, unaffected by leave or holidays
4–6 weeks
From signed scope to delivery starting
Monthly
Cycle to raise or lower committed hours

Questions about assigning a Data Analyst.

How fast can we get answers?

Once access is in place, usually within the first sprint. Access is normally the delay rather than the analysis.

Will you build dashboards nobody uses?

We try not to. Every dashboard should have a named owner and a decision it supports, or it should not exist.

Assign a Data Analyst to your roadmap.

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