Data · Resume guide
Data science resumes are screened for the modeling-to-production spectrum: postings increasingly rank deployment and experimentation evidence (models in production, A/B frameworks) above notebook-only project lists and Kaggle links.
These terms appear repeatedly in real data scientist job descriptions. Use the exact forms below where your experience honestly supports them — exact matches rank; paraphrases often don't.
Share of 195 live data scientist postings in our 15 August 2026 snapshot . Front-load the ones your target job description actually names.
| Skill | Share of postings |
|---|---|
| Python | 64% |
| SQL | 60% |
| Machine Learning | 47% |
| LLM | 16% |
| Spark | 11% |
| R | 10% |
| OpenAI | 9% |
| PyTorch | 9% |
| Snowflake | 8% |
| Looker | 7% |
| Tableau | 7% |
| scikit-learn | 7% |
Public ATS boards (Arbeitnow, Greenhouse, Ashby, Google Careers, Lever, RemoteOK, Remotive). Not LinkedIn or Indeed. Snapshot, not a forecast — always mirror the posting in front of you.
Strong data scientist bullets pair the role's vocabulary with a measured outcome. Use these as patterns — with your real numbers, never invented ones.
“Shipped a churn-prediction model (XGBoost, deployed via MLflow) that targeted retention offers and cut monthly churn 14%”
“Designed the company's A/B testing framework and guardrail metrics, adjudicating 40+ experiments/year across product teams”
Paste the data scientist job description you're targeting and extract its required skills and repeated phrases.
Rephrase your real experience with the posting's exact terminology — same work, their words.
Reorder your summary, skills, and top bullets so this role's priorities lead.
Verify: check your match score and remaining keyword gaps before submitting.
Prioritize models that shipped and metrics they moved over academic breadth — 'deployed', 'in production', and 'A/B tested' are the terms JDs and hiring managers both scan for. Business-impact numbers beat model-accuracy numbers on a resume.
The highest-weight terms for data scientist postings currently include: Python, SQL, Machine Learning, LLM, Spark, R. The definitive list is always the specific job description — paste it into a free keyword check to see exactly which terms your resume shows and which it's missing.
Extract the job description's required skills and repeated phrases, then rephrase your real experience using those exact terms — lead your summary and top bullets with what that posting emphasizes. Never add skills you don't have; keep genuine gaps visible and address them honestly.
Upload your resume, paste the job description, and get your free ATS match score with every missing keyword — then a tailored, ATS-safe rewrite without fabrication.