Free Resume Score and ATS Score Checker

A resume score is a single 0–100 number that rates how well your resume performs against applicant tracking systems and recruiters. It is calculated by weighting several dimensions — parsing and formatting, keyword match, content strength, section coverage, and readability — and combining them into one score. A score of 80 or higher is generally considered strong.

Upload your resume to get an instant 0–100 resume score. See how you rate on parsing, keyword match, content strength, section coverage, and readability — and get the exact fixes that raise your score fastest.

ATS scoreResume parsingKeyword gapsFormatting issuesSection order

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Quick answer: a good ATS score is usually 80+, while 90+ means your resume is cleanly parsed, uses standard sections, and matches the job description keywords without stuffing.

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Upload Your Resume

Drag and drop your PDF, DOC, or DOCX file. Your data stays private — files are encrypted in transit and deleted after analysis.

AI Scores Every Dimension

Our AI rates your resume on parsing and formatting, keyword match, content strength, section coverage, and readability, then weights each into a single 0–100 score.

Get Your Score and Fixes

In under a minute you see your overall score, the breakdown by dimension, your score band, and a ranked list of changes that will raise it the most.

See What Your Report Looks Like

This is a real sample report generated by our AI. Upload your resume above to get your own personalized analysis.

Overall ATS Score

GOOD

Seasoned data science leader with 10+ years delivering ML products, managing cross‑functional teams and generating $10M+ business value across finance, healthcare and tech.

Executive Summary

Top Issues to Fix

×Overlapping employment dates (Nov‑Dec 2020)
×Education dates lack month/year
×Missing key data‑science keywords (feature engineering, statistical modeling)
×No certifications listed

Quick Fixes

✓Fix date overlap and add precise month/year for all roles and degrees
✓Insert missing keywords like "feature engineering" and "ETL" into relevant bullets
✓Add a Certifications section with AWS/Azure credentials
✓Replace generic buzzwords with quantified outcomes

Score Breakdown

section coverage

50%

keyword coverage

70%

content strength

70%

timeline consistency

60%

readability

65%

relevance alignment

75%

Sections Found

✓Summary

✓Technology Stack

✓Professional Experience

✓Education

Missing Sections

!Certifications

!Projects

!Awards

!Volunteer Experience

Keywords Analysis

Hard Skills

Python1

SQL1

Spark1

Databricks2

Snowflake1

Airflow1

Azure3

AWS1

Soft Skills

Leadership2

Collaboration2

Strategic Planning1

Team Building1

Project Management1

Tools & Platforms

Azure3

AWS1

Docker1

Kubernetes1

Domain Terms

Finance1

Healthcare2

Technology2

Retail3

Banking1

Missing Common Keywords

!feature engineering

!statistical modeling

!big data

!ETL

!deep learning

Readability & Content Quality

Avg Sentence Length

On Track

Target range: 12–20 words

Reading Grade Level

On Track

Target range: Grade 8–12 (clear business writing)

Skill Density

Could Improve

Target range: 25–40% of words are skills

Quantification

50%

On Track

Target range: 50–75% bullets with numbers (10/20)

Overused Buzzwords

!cross-functional

!lead

Red Flags

Overlapping employment dates (Nov‑Dec 2020)
Missing month/year for education entries
No certifications listed
Missing key data‑science keywords (feature engineering, statistical modeling)

Priority Recommendations

Priority 1Resolve date overlap and add missing months/years for education

Ensures timeline consistency and ATS parsing

Specify start/end month for each role
Add month/year to degree entries

Priority 2Inject missing high‑impact keywords

Improves keyword match for data‑science director roles

Add "feature engineering" in a bullet
Include "statistical modeling" and "ETL" where relevant

Priority 3Add Certifications section

Demonstrates formal validation of cloud and ML expertise

List AWS Certified Machine Learning – Specialty
List Microsoft Certified: Azure Data Scientist Associate

Priority 4Replace generic buzzwords with concrete metrics

Increases impact and reduces ATS flagging

Swap "cross‑functional" with specific team names
Quantify "lead" with team size or % improvement

Keyword Injection Plan

feature engineering

Director of Data Science bullet

“Implemented feature engineering pipelines that boosted model accuracy by 12%.”

statistical modeling

Manager Data Science bullet

“Led statistical modeling projects that identified $3M cost‑saving opportunities.”

ETL

Senior Data Analyst bullet

“Designed ETL processes that reduced data latency by 40%.”

Bullet Point Rewrites

Before

Spearheaded the design and launch of a proprietary demand forecasting platform used by Fortune 500 retailers.

After

Launched a demand‑forecasting platform adopted by Fortune 500 retailers, increasing forecast accuracy by 15%.

Before

Collaborated with product, engineering, and marketing to align data initiatives with business goals.

After

Aligned data initiatives with product, engineering, and marketing, accelerating go‑to‑market speed by 20%.

Before

Built a centralized data science function and hired a high‑performing team of 6 professionals.

After

Established a data science function and recruited a team of 6, cutting project ramp‑up time by 30%.

Recommended Sections

Certifications

• AWS Certified Machine Learning – Specialty (2021)

• Microsoft Certified: Azure Data Scientist Associate (2022)

Projects

• Real‑time fraud detection system: reduced false positives by 40% and saved $1.2M annually

• Demand forecasting platform: improved forecast accuracy by 15% for a Fortune 500 retailer

Employment Timeline Analysis

Career Progression

Clear upward trajectory from analyst to senior roles, then to manager and director, demonstrating growing leadership and impact.

Employment Gaps Detected

Oct 2018 - Dec 20183‑month gap between Senior Data Analyst and Senior Data Scientist

Overlaps Detected

Jan 2019 – Dec 2020 (Senior Data Scientist) overlaps Nov 2020 – Jan 2022 (Manager Data Science) — 2‑month overlap Nov‑Dec 2020

Timeline ConsistencyDates Present

Analysis based solely on provided plain‑text content; dates inferred where not explicit.

What You'll Get

Upload your resume and receive a comprehensive, AI-powered report covering every angle.

0–100 Resume Score

Get one clear number that tells you, at a glance, how strong your resume is — calculated from parsing, keywords, content, sections, and readability all in a single weighted score.

Dimension Breakdown

See your score split across each scoring dimension so you know whether keywords, formatting, content strength, or section coverage is dragging your total down.

Score Band Rating

Find out which band your resume falls into — needs work, fair, strong, or excellent — so you instantly know whether it's ready to submit or needs another pass.

Keyword Match Score

See how closely your resume matches the hard skills, tools, and role-specific terms employers and ATS software look for — and which keywords are missing.

Prioritized Score Boosters

Get a ranked list of the highest-impact fixes — the changes most likely to move your score the furthest, ordered so you tackle the biggest wins first.

Re-Score After Edits

Make your fixes and re-score in seconds to confirm your changes actually raised the number before you apply, instead of guessing whether they helped.

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Everything You Need to Know About Your Resume Score

How Is a Resume Score Calculated?

A resume score condenses several measurements into one 0–100 number. The scorer evaluates each dimension separately — parsing and formatting, keyword match, content strength, section coverage, and readability — gives each a sub-score, multiplies it by a weight that reflects its importance, and sums the results. Parsing and keywords typically carry the heaviest weight because they determine whether automated screening passes your resume along at all. The output is a single, comparable number you can track as you make edits.

What Is a Good Resume Score?

On a 0–100 scale, 80 or higher is generally considered strong and ready to submit, and 90+ is excellent for competitive roles. Scores in the 60–79 range are fair — the resume usually parses but still has keyword gaps, weak bullets, or minor formatting issues. Below 60 signals real problems worth fixing before you apply. The bands matter more than chasing a perfect 100: a clean, relevant resume that scores 88 beats a keyword-stuffed one gaming a higher number.

The Scoring Dimensions Explained

Five dimensions drive most resume scores. Parsing and formatting checks whether software can read the file cleanly, free of tables, columns, and headers that garble text. Keyword match measures how well your skills and terms align with the target role. Content strength rewards action verbs and quantified achievements over vague duties. Section coverage confirms standard sections like Experience, Education, and Skills are present and ordered correctly. Readability rates clarity, length, and scannability for the human recruiter. Your weakest dimension is almost always where the biggest score gains hide.

Why Scores Differ Between Tools

The same resume can score differently across tools because each one defines and weights dimensions its own way, uses a different keyword library, and may or may not compare against a specific job description. One scorer might weight keywords at 35% and another at 20%; one might penalize a two-page resume while another doesn't. None of these is wrong — they're just different rubrics. The practical takeaway is to pick one tool, use it consistently to measure progress, and pay attention to the dimension breakdown rather than fixating on the absolute number.

How to Improve Your Resume Score

Improve your score by working the dimensions in order of impact. First clear parsing blockers — switch to a single-column layout with standard headings and remove tables, text boxes, and images. Next, raise keyword match by mirroring the most important terms from the job description where they genuinely apply. Then strengthen content by rewriting responsibility-style bullets into quantified achievements. Finally, fill any missing sections and tighten wording for readability. Re-score after each change so you can see exactly which edits moved the number.

Resume Score vs. Interview Outcomes

A resume score predicts how well your resume clears automated screening and a recruiter's first glance — not whether you'll get hired. A strong score means your resume is well-constructed, so it's far more likely to reach a human and make a good first impression. But interview decisions also weigh how closely your real experience fits the role, the strength of the candidate pool, timing, and referrals. Think of the score as removing avoidable rejections, not as a forecast of the final result.

Is a High Resume Score Enough?

A high score is a quality floor, not a finish line. It confirms your resume parses cleanly, covers the right keywords, and reads well — clearing the hurdles that silently reject most applicants. But once your resume is in a recruiter's hands, substance takes over: the achievements have to be real, relevant, and compelling for the specific job. The right approach is to push your score into a strong band, then stop optimizing for the number and make sure the resume tells an honest, targeted story that earns the interview.

Who Is This For?

Whether you're just starting out or leveling up, this tool is built for you.

📊

Data-Driven Applicants

Replace guesswork with a concrete 0–100 number and only hit submit once your resume clears a strong score band.

🔄

Career Changers

See how your resume scores against a new field's keywords and close the gaps before recruiters in that industry ever see it.

🎓

Students & New Grads

Get an objective rating of a first resume and know exactly which dimensions to strengthen before your first applications.

Why Use the Resume Score?

Most job seekers have no objective way to know if their resume is good enough to submit. A resume score turns a vague gut feeling into a concrete 0–100 number you can act on. Our free Resume Score Checker reads your resume the way modern ATS software and recruiters do, scores it across the dimensions that matter, and shows exactly which ones are holding you back — so you can fix the weakest dimensions, watch the number climb, and only apply once it clears a strong band.

⚡

Instant Results
Get your report in under 30 seconds

🔒

100% Private
Files encrypted and auto-deleted

💰

Completely Free
No credit card or signup needed

What People are Saying?

Trusted by thousands of professionals — here's how Resumly helped them succeed

Nina Patel

Data Analyst at HealthFirst

Resumly tailored my resume with clear metrics and tools I use. Interview preparation made case questions easy, and I accepted an offer at HealthFirst.

Amara Singh

HR Generalist at Marriott Corporate

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Daniel Rossi

Sales Operations Specialist at Salesforce

Tailored cover letters plus auto apply meant more responses. I leveled up to a revenue operations role faster than expected.

Diego Rivera

Education Program Coordinator at Riverside Schools

Tailored cover letters made each application resonate. Interview preparation gave me confident, concise answers for panels.

Robert King

Procurement Analyst at Procter & Gamble

Auto apply expanded my reach. The tailored resume highlighted cost savings and vendor performance—interviews followed fast.

Jason Kim

Product Manager at Shopify

Tailored cover letters helped me tell the right story. Auto apply saved hours so I could focus on interview preparation for PM case rounds.

Lucas Martin

Financial Analyst at JPMorgan

Tailored resumes focused on valuation and modeling. With interview preparation, I felt ready for technicals and secured the offer.

Olivia Chen

Project Manager at IBM

Resumly tailored my resume for PMP‑style accomplishments. Interview preparation made stakeholder and risk questions straightforward.

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Public Relations Specialist at UNICEF

Resumly’s tailored resume emphasized media placements and impact. Auto apply helped me reach mission‑aligned roles quickly.

Emily Wang

Legal Assistant at City Attorney's Office

Tailored cover letters and interview preparation helped me present casework clearly. The process felt simple and effective.

Maria Lopez

Marketing Manager at Unilever

The tailored resume emphasized campaign ROI and growth. Interview prep refined my STAR answers—I moved up to a manager role quickly.

Aisha Khan

Operations Coordinator at FedEx Office

Auto apply simplified applications across roles. Resumly’s tailored resume highlighted process improvements—callbacks tripled in a week.

Michael Adams

Customer Success Manager at HubSpot

The tailored resume showcased retention wins and playbooks. Interview prep refreshed my discovery questions—offer accepted.

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IT Support Specialist at Amazon

The tailored resume mapped my skills to job descriptions. Interview preparation improved my troubleshooting narratives.

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Resumly tailored my resume to HR priorities—onboarding, ER, and reporting. Auto apply cut the application time in half.

Ethan Zhao

Business Analyst at Deloitte

Auto apply handled multiple postings. Resumly’s tailored cover letters and interview preparation led to back‑to‑back final rounds.

Sarah Green

UX Designer at Microsoft

The tailored resume showcased outcomes and user impact. Interview preparation sharpened my portfolio walkthrough and whiteboard skills.

Priyanka Verma

Healthcare Operations Analyst at Mayo Clinic

Resumly highlighted analytics, EMR, and process improvement. Tailored cover letters and interview prep got me over the line.

Lena Petrova

Data Scientist at Spotify

Resumly tailored my resume for ML projects and business impact. Tailored cover letters and interview prep led to multiple offers.

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Communications Specialist at Red Cross

Tailored resumes and cover letters showcased outcomes across campaigns. Interview preparation made panel interviews stress‑free.

Nina Patel

Data Analyst at HealthFirst

Resumly tailored my resume with clear metrics and tools I use. Interview preparation made case questions easy, and I accepted an offer at HealthFirst.

Jason Kim

Product Manager at Shopify

Tailored cover letters helped me tell the right story. Auto apply saved hours so I could focus on interview preparation for PM case rounds.

Maria Lopez

Marketing Manager at Unilever

The tailored resume emphasized campaign ROI and growth. Interview prep refined my STAR answers—I moved up to a manager role quickly.

Resume Score — Frequently Asked Questions

Find answers to the most common questions about the Resume Score

A resume score is a single 0–100 number built by scoring several dimensions and combining them with weights. Typical dimensions are parsing and formatting, keyword match against the target role, content strength (action verbs and quantified results), section coverage, and readability. Each dimension is scored 0–100, multiplied by its weight, and summed into your overall score.

A good resume score is generally 80 or higher on a 0–100 scale. Scores of 80–89 are strong and usually ready to submit, while 90+ is excellent and best for competitive roles. Scores of 60–79 are fair but still have keyword or formatting gaps, and anything below 60 needs meaningful work before applying.

Bands group scores into plain-English ratings. Below 60 means your resume needs work and likely has parsing or content problems. 60–79 is fair — it parses but has gaps. 80–89 is strong and generally ready to apply. 90–100 is excellent, with clean parsing, strong content, and tight keyword alignment for the target role.

A 75 is a fair score but not yet strong. The resume probably parses and covers the basics, but you likely have missing keywords, weak or unquantified bullet points, or minor formatting issues. Aim to get above 80 before applying, and 90+ for highly competitive roles.

They overlap heavily and the terms are often used interchangeably. An ATS score focuses on whether applicant tracking software can parse and rank your resume. A resume score is broader — it includes ATS parsing and keywords but also weighs content strength and readability for the human recruiter who reads it after the ATS.

Weighting reflects what most affects your odds. Parsing and formatting and keyword match usually carry the most weight because they decide whether your resume survives automated screening at all. Content strength and section coverage come next, and readability rounds it out. The exact weights vary by tool, but parsing and keywords almost always dominate.

Start with the lowest-scoring dimension. Fix parsing blockers like tables, columns, and headers first, then add the role keywords you're missing, rewrite weak bullets into quantified achievements, make sure all standard sections are present, and tighten wording for readability. Re-score after each change to confirm the number went up.

Different resume scorers use different dimensions, weights, and keyword libraries, and some compare your resume to a specific job description while others score it in isolation. That's why the same resume can read 72 on one tool and 85 on another. Use one tool consistently to track progress, and treat the dimension breakdown as more useful than the raw number.

Yes, if the tool compares your resume to one. Pasting a target job description sharpens the keyword match dimension, so your score reflects that specific role rather than a generic baseline. A resume can score well against one posting and lower against another that emphasizes different skills.

No. A high score means your resume is well-built — it parses cleanly, covers the right keywords, and reads strongly — which clears the automated and first-glance hurdles. But interviews also depend on how well your actual experience fits the role, competition, timing, and the recruiter's judgment. A high score improves your odds; it doesn't guarantee the outcome.

A high score is necessary but not sufficient. It gets you past ATS filters and into the recruiter's hands, but the resume still has to tell a convincing, relevant story. Treat the score as a quality floor — clear it, then make sure your achievements genuinely match the job you want.

Yes, it's completely free. Upload your resume and get your full score and breakdown with no credit card and no signup required.

You can upload PDF, DOC, or DOCX files. A simple text-based PDF or DOCX with standard sections scores most reliably, since complex layouts can hurt the parsing dimension.

Check it whenever you tailor your resume for a new role, and re-check after every round of edits. Because keyword match depends on the target job, a resume that scores well for one posting may need work for another.