← All resourcesWhat recruiters look for first
A data analyst resume gets ranked in seconds. These are the five signals a recruiter (and an LLM-ranked ATS) checks before deciding whether to keep reading.
- SQL named on the top line (often a hard filter)
- BI tool named: Looker, Tableau, Mode, Hex, Metabase
- At least one decision a stakeholder made because of your work
- Statistics + experimentation methods if relevant
- Domain expertise (marketing, finance, growth, ops) called out if you have it
Bullet patterns that work
Every strong data analyst bullet follows the same shape: action verb → what you built → who it was for → a number that proves the impact. Use these patterns as a scaffold, not a script.
Pattern
Analyzed [data] for [stakeholder], driving [decision] that [outcome]Example
Analyzed funnel dropoff for the growth team, identifying a confusing email confirmation step that drove a redesign that lifted activation by 7%
Pattern
Built [dashboard / report] used weekly by [team], replacing [manual process]Example
Built a self-serve cohort dashboard in Looker used weekly by Sales, CS, and Product, replacing 3 separate spreadsheet handoffs
Pattern
Designed [experiment] that [proved or disproved hypothesis]Example
Designed a holdout-controlled email experiment across 60k users that disproved a planned re-engagement campaign, saving an estimated 4 weeks of build effort
Skills section — what to keep
Recruiters skim skills sections for the keywords the JD mentioned by name. Lead with the hard skills, group your tools, and keep soft skills short.
Hard skills
- SQL
- Experiment design
- Funnel analysis
- Cohort analysis
- Statistical inference
- Data visualization
Tools
- SQL
- Looker
- Tableau
- Mode
- Hex
- Snowflake
- BigQuery
- Python
- R
Soft skills
- Stakeholder partnership
- Storytelling with data
Pitfalls that get data analysts filtered
- Listing "Excel" before SQL — Excel is assumed
- Skipping the stakeholder decision attached to each analysis
- Calling yourself analyst with no SQL on the resume
- Listing every BI tool you've touched instead of the one you've owned
Frequently asked
Is Tableau or Looker more in demand in 2026?
Both still in demand. Looker has grown in tech-forward orgs; Tableau dominates enterprise. List the one you've shipped against most recently.
Do I need Python for analyst roles?
SQL is the floor. Python (or R) is a strong plus for any analyst role with experimentation or modeling work.
How is data analyst different from data scientist?
Analyst usually owns reporting + ad-hoc analysis + experimentation support. DS leans more on modeling. Tier carefully — analyst-leveled roles usually expect less ML, more SQL.
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