Field guide
How ATS screens data and analytics resumes
Data roles are screened on tools and methods together. A recruiter wants SQL and Python, but also the methods: A/B testing, forecasting, regression, dimensional modeling, named the way the posting names them.
What recruiters filter and search on
- Query and programming tools: SQL, Python or R, and the warehouse (Snowflake, BigQuery, Redshift)
- BI tools named in the posting: Tableau, Power BI, Looker
- Methods: experimentation, forecasting, statistical modeling, ETL or ELT
Name things the way the posting does
- Write the method, not just the outcome: "ran A/B tests" rather than "improved conversion"
- Name the warehouse and the orchestration tool (dbt, Airflow) if you used them
- Quantify scale: rows, tables, dashboards, stakeholders served
What trips up parsers in this field
- Charts or dashboards pasted into the resume as images
- Methods described in prose with no tool named
- A long tool list with no bullet showing what you did with each
How PassMyResume scores this field
Keywords 60%, credentials 5%, formatting 20%, content alignment 15%. Credentials only count when the posting requires one; otherwise that weight moves to keywords. The full formula.
The scanner knows 220 terms specific to this field, such as Alteryx, Qlik Sense, QlikView, SAS, SPSS, and credentials like Google Data Analytics Professional Certificate, Google Advanced Data Analytics Professional Certificate, Google Business Intelligence Professional Certificate.
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