Data Scientist resume — templates, keywords, and bullet examples
Data scientist resumes are scanned for tooling specificity (Python, SQL, PyTorch, Snowflake) AND a clear thread of business outcome. Many resumes do one but not both.
How to angle a data scientist resume
The trap on data science resumes is to fill them with model-architecture detail no recruiter understands. The fix is the "business outcome first, model second" pattern: "Cut churn 4% with a gradient-boosted model on Snowflake feature store" beats "Built a gradient-boosted model".
Senior DS candidates: lead the Summary with experimentation rigor (causal inference, A/B platform ownership) — that's the senior signal recruiters care most about.
Section order: Summary → Experience → Projects → Education → Skills (split into Languages / ML / Tools).
Recommended templates for data scientists
ATS keywords recruiters filter on
These are the keywords most data scientist JDs use as their ATS-filter inputs. Make sure the ones you genuinely have evidence for are in your Skills section.
Starter Skills section
Paste this into the Skills section of the editor as a starting point, then prune to what you genuinely have evidence for.
Bullet examples you can adapt
Three starter bullets following the action-verb / quantified-outcome pattern. Replace bracketed placeholders with your actual specifics — never invent.