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Data Scientist ATS keywords

Recruiters and Applicant Tracking Systems score Data Scientist resumes by keyword match against the job description. Use these keyword groups as a starting point, then mirror the exact phrasing of the posting you are applying to.

Core ATS keywords

machine learningstatistical modelingPythonpredictive analyticsbig dataAWS

Role skills (from the data scientist resume example)

Machine learningStatistical modelingPythonBig data technologiesPredictive analyticsAWS cloud

Hard skills

Machine learningStatistical modelingPythonBig data technologiesPredictive analyticsAWS cloud

Soft skills

stakeholder managementcross-functional collaborationownershipprioritizationwritten communicationverbal communicationtechnical debuggingcode review

Tools & platforms

PythonJupyterscikit-learnPyTorchTensorFlowSQLAirflowMLflow

Certifications to consider

AWS Machine Learning SpecialtyTensorFlow Developer Certificate

How to use these keywords

  1. Copy the job description you are applying to and highlight every noun/phrase that appears more than once — those are the Data Scientist keywords ATS weights most heavily.
  2. Aim for a 75–85% keyword match. Below 60% your resume is probably being filtered out; above 85% you are well-positioned.
  3. Do not keyword-stuff. Integrate terms naturally into bullet points that describe real outcomes.
  4. Use both the full phrase and the acronym where relevant (e.g. "Customer Relationship Management (CRM)") — different ATS parsers tokenize differently.
  5. Run the final resume through the free ATS resume checker before submitting.

Skip the guessing — check the exact keyword gap

Paste your resume and a data scientist job posting — get a free ATS score and see which keywords are missing.

Free ATS resume checkerSee Data Scientist resume example

Common questions

What are the most important ATS keywords for a Data Scientist resume?

The most important ATS keywords for a Data Scientist resume are the ones that appear in the specific job description you are applying to — but machine learning, statistical modeling, Python are the baseline Data Scientist terms that show up in most postings.

How many ATS keywords should a Data Scientist resume have?

Target 15–25 role-specific keywords across your summary, skills, and experience sections. Density matters less than placement — keywords in the top half of the first page carry more weight.

Should I list keywords in a separate "keywords" section?

No — ATS parsers flag keyword-stuffed sections and recruiters ignore them. Weave keywords into natural prose inside your summary, skills, and bullet points.

How do I know which Data Scientist keywords a specific job uses?

Paste your resume and the job description into the free ATS resume checker. It extracts the keyword gap automatically, showing exactly which Data Scientist phrases the posting uses that your resume is missing.