Data Scientist resume skills. The words recruiters search for.
The 17 skills and tools that come up in data scientist job posts, sorted by type, and how to put them in bullets a recruiter believes.
By Nazir Elmurodov, Founder, LaunchCV · Updated
/ The list
Keywords by type. Use only the ones that are true for you.
Hard skills · 10
- Python (used in Arjun's sample resume)
- R
- SQL (used in Arjun's sample resume)
- Machine learning
- Statistics (used in Arjun's sample resume)
- A/B testing (used in Arjun's sample resume)
- Causal inference (used in Arjun's sample resume)
- Feature engineering
- Deep learning
- NLP
Tools & software · 7
- scikit-learn (used in Arjun's sample resume)
- TensorFlow
- PyTorch (used in Arjun's sample resume)
- XGBoost (used in Arjun's sample resume)
- Spark (used in Arjun's sample resume)
- MLflow (used in Arjun's sample resume)
- AWS (used in Arjun's sample resume)
11 of 17 appear in Arjun's sample resume. See where
/ How to use them
Put keywords in bullets, not just in a skills list.
A skills list tells the software you have a skill. A bullet shows a recruiter what you did with it.
Python
Weak: Skills: Python
Strong: Design and analyze 20+ experiments a year using a shared Python framework for power analysis
MLflow
Weak: Skills: MLflow
Strong: Deployed batch and real-time models with MLflow and Docker, with automated drift monitoring
Spark
Weak: Skills: Spark
Strong: Cut weekly model retraining from 6 hours to 40 minutes by moving feature pipelines to Spark
Python, SQL
Weak: Skills: Python, SQL
Strong: Wrote SQL and Python pipelines feeding 15 production dashboards
Strong bullets come from Arjun's sample resume and our data scientist bullet examples. Names and figures are illustrative.
/ Use them honestly
Keywords get you found. Proof gets you hired.
Mirror the job post's wording for skills you really have. If a data scientist post asks for Python and you've used it, say Python, in the post's spelling, and show where.
Mirror the job post's wording
If a data scientist post says "R", write "R", not a near-synonym — as long as it's accurate. Recruiters search for the post's exact term.
Only claim what you can back up
Expect to be asked about every term you list. If you couldn't spend two minutes on Python — what you did and what changed — leave it out.
Show it in a bullet
A skills list says you know Python. A bullet like the one under Data Scientist in the example above shows what you did with it.
No stuffing, no hidden text
Repeating a word or hiding keywords in white text doesn't make you a better match. A person reads the resume in the end.
Which of these does your resume say?
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/ Questions
Data Scientist keywords, answered.
Something else? support@launch-cv.com
How many keywords should a data scientist resume have?
There's no magic number. Arjun's sample resume uses 11 of the 17 terms on this page — the ones that fit that job. Cover what your post asks for that you can back up, each where it fits; repeating a keyword doesn't help.
Should I copy keywords exactly from the job post?
Use the post's wording for skills you really have. If a data scientist post says "Python", write "Python" rather than a synonym, so a recruiter searching for that term finds you. Don't add skills you don't have just because the post lists them.
Where should keywords go on my resume?
In your summary, a short skills section and, above all, the bullets under each job, where you show what you did with the skill. In Arjun's sample, Python shows up in a bullet under Data Scientist. Plain text in the body of the page is easiest for applicant tracking systems to read.
Which tools should I list on a data scientist resume?
The ones you've used and the post mentions. Common ones in data scientist posts include scikit-learn, TensorFlow, PyTorch, XGBoost and Spark. Name the tool in the bullet where you used it, not only in the skills list.
Keywords for related roles
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