ATS Keywords for
Machine Learning Engineer / Data Scientist Resumes
23 terms across 5 groups, from our 2026 research into how recruiters actually source Machine Learning Engineer / Data Scientist candidates. Recruiter and ATS searches match exact strings — carry the terms your real experience supports, in the wording the posting uses. Never list a term you couldn't back up in an interview: keyword stuffing fails the interview it wins.
The Machine Learning Engineer / Data Scientist keyword bank
Titles
- Machine Learning Engineer
- Data Scientist
- ML Engineer
- Applied Scientist
Modeling & technique
- gradient boosting (XGBoost)
- deep learning (PyTorch)
- causal inference
- uplift modeling
- A/B testing
Production & MLOps
- model deployment
- feature stores
- MLflow
- model monitoring
- batch and real-time inference
Languages & tools
- Python
- SQL
- scikit-learn
- TensorFlow
- Spark
Outcomes
- forecast accuracy
- churn reduction
- decision automation
- statistical significance
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Writing about Machine Learning Engineer / Data Scientist careers? Paste this self-contained snippet into your post — free to use with the credit link included.
Your next step
Copy the terms that are genuinely true of your experience, then run the free match checker — it shows exactly which of the posting's terms your resume covers and which are missing.
- Carry the same terms into LinkedIn → recruiters run the same searches there — the optimizer builds your headline and About around them.
How recruiters use these terms
Recruiters run Boolean searches that OR together title variants and AND them with must-have skills, then ATS platforms rank applications by how literally the resume matches the posting. That's why the exact product name, certification code, or title variant matters: "SIEM experience" doesn't match a search for a specific platform name, and a title variant you never carry is a search that never finds you. Work the honest terms into your headline, summary, skills block, and experience bullets — placement near the top of page one carries more weight than repetition.
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