Key Takeaways

  • 75% of U.S. employers use automated applicant tracking systems to screen resumes before a human reviews them (Harvard Business School & Accenture, 2021)
  • The most common ATS failures are missing keywords, incompatible formatting, and incorrect file types
  • ResumeGeni scores your resume across 8 parsing layers — modeled on the same steps enterprise ATS platforms like Workday, Greenhouse, and Taleo use to evaluate candidates

How ATS Resume Scoring Works

Applicant tracking systems parse your resume into structured data — extracting your name, contact info, work history, skills, and education — then score how well that data matches the job requirements. Many ATS rejections happen because the parser couldn't extract critical fields, not because the candidate wasn't qualified.

LayerWhat It ChecksWhy It Matters
Document extractionFile format, encoding, readabilityCorrupted or image-only PDFs fail immediately
Layout analysisTables, columns, headers, footersMulti-column layouts break field extraction
Section detectionExperience, education, skills headingsNon-standard headings cause sections to be missed
Field mappingName, email, phone, dates, titlesMissing contact info is a common cause of immediate rejection
Keyword matchingJob-specific terms, skills, certificationsKeyword overlap affects recruiter search visibility and ATS scoring
Chronology checkDate ordering, gap detectionReverse-chronological order is expected by most ATS
QuantificationMetrics, numbers, measurable outcomesQuantified achievements help human reviewers and some scoring models
Confidence scoringOverall parse quality and completenessLow-confidence parses get deprioritized in results

Frequently Asked Questions

Is ResumeGeni free?
Yes. ResumeGeni is currently in beta — ATS analysis, scoring, and initial improvement suggestions are free with no signup required. Full guidance and saved reports may require a free account.
What file formats are supported?
PDF, DOCX, DOC, TXT, RTF, ODT, and Apple Pages. PDF and DOCX are recommended for best ATS compatibility.
How is the ATS score calculated?
Your resume is processed through an 8-layer parsing pipeline that extracts structured data the same way enterprise ATS platforms do. The score reflects how completely and accurately your resume can be parsed, plus how well your content matches common ATS ranking criteria.
Can ATS read PDF resumes?
Yes, but not all PDFs are equal. Text-based PDFs parse well. Image-only PDFs (scanned documents) and PDFs with complex tables or multi-column layouts often fail ATS parsing. Our analyzer will flag these issues.
How do I improve my ATS score?
Focus on three areas: use a clean single-column format, include keywords from the job description naturally in your experience bullets, and ensure all sections (contact, experience, education, skills) use standard headings.

ATS Guides & Resources

Built by engineers with 12 years of experience building enterprise hiring technology at ZipRecruiter. Last updated .

Senior Data Engineer

Perionnetworkltd · Tel Aviv, Israel

Perion is a global advertising technology company delivering solutions to the biggest brands and publishers around the globe across search, social media and display, video, CTV, and programmatic DOOH.

Home to an award-winning technology solution –– with our unique data-driven AI/ML based technologies, we deliver and optimize hundreds of terabytes of data and billions of events per day. We’re working with dozens of sources to provide a superior experience across screens and platforms, including mobile, video, social and native.


We are looking for a highly enthusiastic Data Engineer to join our group on the journey of leveraging Big Data to revolutionize our offering, business operations and decision making across the company’s ecosystem.

Job Responsibilities:

  • Design, build & deploy backend data solutions to prod, starting from research and design to development and testing.
  • Work closely with data engineers, product, architects and other R&D teams to deliver the best solutions to the business.
  • Monitor the solutions in production to make sure they are fully stable, scalable and performant at all times.
  • Work closely with data sciences experts

Profile and Experience:

  • At least 3 Years of proven hands on experience with big data solutions and frameworks in production (Spark, Flink) – mandatory
  • Proven ability of writing complex SQL queries – mandatory
  • Strong analytical and problem-solving skills with attention to details - mandatory
  • Production grade experience of writing spark applications using Scala or Java - mandatory
  • Experience with Apache Airflow and AWS tools (EMR, Glue, Athena) – a big advantage
  • Solid knowledge in Python and Linux operating systems – a big advantage
  • Experience with Clickhouse – a big advantage
  • Familiarity with the Ad Tech industry and RTB – an advantage
  • Extensive experience in Functional programming, Unit testing/TDD, continuous Deployment – an advantage
  • Familiarity with NodeJS - an advantage
  • Fluent verbal and written English skills required