// tech resume guide · 2025
Everything a data scientist needs to clear the ATS, get the recruiter's 6-second scan, and land the interview — examples, keywords, and the exact phrases hiring managers in tech want to see.
12 min read · last updated 2025
// table of contents
// the problem
Here's the hard truth: 75% of resumes for tech roles never reach a human. They die in an Applicant Tracking System (ATS) — Workday, Greenhouse, Lever, Taleo — that's looking for specific keywords, structure, and signals. Data Scientists get filtered for three reasons, over and over:
Reason 1
Models described without business impact
Reason 2
Missing 'A/B testing' and 'experimentation' keywords
Reason 3
Toolchain buried in a skills list ATS won't weight
Fix those three, and you're already ahead of 80% of the applicant pool. The rest of this guide tells you exactly how.
// structure
ATS systems parse top-to-bottom. Recruiters scan in the same order. Use this exact structure — no creative reorderings, no two-column layouts (they break ATS parsing completely).
Header
Name, city/state, phone, email, LinkedIn URL. No photo, no graphics, no fancy fonts. ATS systems can't read images and most will reject the whole document.
Professional summary
3-4 lines, written for the specific role. Lead with your strongest credential as a data scientist (years of experience, top employer, biggest win). Mirror the job title from the JD.
Experience
Reverse chronological. Each role: company, title, dates (MM/YYYY), then 4-6 bullets. Each bullet starts with a strong verb and contains a number. We'll show examples below.
Skills
A flat list of the technical and tool keywords for data scientist roles. NOT a graphic with star ratings. Plain text, comma-separated, in the order the JD lists them.
Education + certifications
Degree, school, year. Certifications matter less in tech but list them if relevant.
// keywords
We scraped thousands of data scientist job descriptions across LinkedIn, Indeed, and Greenhouse to find the keywords that appear most often. If you have real experience with these, they belong in your resume — verbatim, in your bullets and skills section. Don't paraphrase ("worked with relational databases" → write "PostgreSQL").
⚠️ Don't keyword-stuff. ATS systems flag obvious keyword density. The trick is weaving them into bullets that show real impact — exactly what RewriteHire does automatically.
// before & after
This is the difference between a resume that gets filtered and one that gets a recruiter screen. Same role, same person — totally different signal.
Before — generic
Built churn model using machine learning techniques.
After — tailored for Senior Data Scientist at Airbnb
Shipped XGBoost churn model (AUC 0.89) in Python + Snowflake; A/B test drove $2.4M ARR retention lift across 180k accounts.
Why the second one wins
// what to cut
"Responsible for…" — Cut every instance. Lead with verbs that show action: built, shipped, scaled, owned, drove.
Skills as graphics or star ratings. ATS reads them as zero. Plain text only.
Two-column layouts. Most ATS systems read column 1 top-to-bottom, then column 2 — your bullets get scrambled.
Generic objective statements ("Seeking a challenging role…"). Replace with a 3-line summary tailored to the JD.
Listing every job back to college. Cap at 10-15 years for senior roles, less for junior.
No metrics. If a bullet has no number, it has no weight. Add headcount, dollars, percentages, or scale.
One resume for every job. ATS scoring is JD-specific. Tailor or watch your match score plummet.
// numbers that matter
A bullet without a number is a bullet without weight. Here's what to quantify on a data scientist resume:
// summary section
Recruiters spend 6 seconds on the first scan. Your summary is the only paragraph they actually read. Use this 3-line formula:
Template
Line 1: [Title] with [X years] in [industry/specialty].
Line 2: Built/shipped/led [biggest measurable win].
Line 3: Looking for [type of role] where I can [outcome they care about].
Example — Senior Data Scientist at Airbnb
Data Scientist with [X] years in tech. Shipped XGBoost churn model (AUC 0.89) in Python + Snowflake; A/B test drove $2.4M ARR retention lift across 180k accounts. Looking for a data scientist role where I can drive measurable impact on [outcome they care about].
// see your real ATS score
Paste your resume + a real data scientist JD. We'll show your ATS score, which keywords you're missing, and what to fix — free, no signup.
// other guides