Data Scientist resume keywords, ranked from real postings
Not a generated synonym list — this is how often each term actually shows up across Data Scientist postings in our live crawl, ranked by the share of postings that mention it.
Not enough live postings yet for this role
We only publish a frequency table once we've analyzed enough postings — fewer than that reads as data when it's really a coin flip. In the meantime, Data Scientist postings consistently ask for: Python, pandas / NumPy, scikit-learn, SQL, Machine learning, Statistical modeling, A/B testing / experimentation, Feature engineering. That list is written by hand from common requirements in the field, not machine-generated — see the full Data Scientist check for the complete breakdown.
See this against your own resume
Paste a specific Data Scientist posting and your resume to see your match score and exactly which of its requirements you don't evidence yet — free, no account.
Check my resume for this roleHow this list is built
Every posting we crawl for Data Scientist roles runs through the same rule-based extractor SteadyCV's resume check uses — no LLM, no invented terms. A term only counts if it's confidently identified in the posting text itself: a named tool, an acronym, something inside the requirements section — not guessed from context. We rank by how many distinct postings mention a term, not how many times it's repeated in one, so a single wordy posting can't dominate the list.