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 .

Data Science Engineer

Apiiro · Tel Aviv-Yafo, Tel Aviv District, Israel

Join Apiiro — Design, develop, and deliver secure software faster

Apiiro is a fast-growing startup at the forefront of the application security field. Our cutting-edge platform is designed to help development teams build secure software quickly, enabling them to move faster while managing risks. As pioneers in the app-sec space, we’re shaping the future of secure software development. If you're looking for an exciting opportunity to make a significant impact and grow with a passionate team, Apiiro is the place to be.

 

About the Team

Our team focuses on delivering cutting-edge, AI-powered automated application security features within our ASPM product. We are a dynamic, agile team emphasizing seamless transitions from design to production, deployment, and ongoing monitoring. We excel at operationalizing machine learning, data science, and AI solutions into robust, secure, and high-performance security capabilities.

 

What You Will Do

  • Be a core member of a cross-functional AI innovation team, collaborating closely with software engineers, MLOps specialists, and analysts.
  • Design, build, and optimize end-to-end AI-driven features - from experimentation and model training to validation and deployment.
  • Develop production-grade code (Python and C#) to integrate advanced models and data-driven capabilities into our core products.
  • Continuously evaluate model performance and data quality in real-world settings, proactively driving improvements, retraining, and robust monitoring

 

What You’re About

  • B.Sc. in Computer Science, Mathematics, or similar.
  • 4+ years of hands-on experience in applied data science or machine learning roles.
  • Experience with building solutions based on agents, LLMs, generative AI, and advanced AI/ML frameworks.
  • Proficient in writing clean, maintainable, and efficient Python code.
  • Optional (preferred):
    • Experience with additional languages such as Java or C#.
    • M.Sc. in Computer Science, Mathematics, or similar.
  • Independent, proactive, and agile.
  • Skilled at problem-solving and creative solution-finding.
  • Strong teamwork and communication skills; thrive in highly collaborative, diverse teams.
  • Innovative and committed to continuous learning and staying up-to-date with the latest technologies.