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 Scientist

Myob 2 · Melbourne, Australia

We’re a leading business management solution with a core purpose: helping more businesses in Australia and New Zealand start, survive and succeed. At MYOB, we believe what’s good for one business is good for all business—and for all of us. Whether you support them, work for them, or dream of building your own, when businesses run smoothly, everybody feels it. Owners, employees, customers, suppliers—even families. That’s why we’re here: to give every person in business the tools they need to focus on what really matters and do Big Things—whatever big looks like for them. And for you? Joining MYOB means being part of that impact. It means using your skills to help businesses thrive, shaping the future of work, and growing alongside the people and communities we support. Because while we’re the business of software, we’re really in the business of people. And that makes MYOB Everyone’s Business. About the role Join our Data and AI team and help build features that actually make a difference for MYOB's customers. As a Data Scientist, you’ll take ideas from hypothesis all the way to production — prototype → MVP → scale — with clear metrics, robust offline testing, and live A/B experiments to prove impact. You’ll work with product managers, engineers, and designers to frame the right problems, choose the right methods (think transformers, recommenders, time series), and deliver AI that’s scalable and maintainable. We’re looking for someone who leads with an experiment-first mindset, champions responsible AI, and helps lift the whole team through mentoring and knowledge sharing. The skills you'll need: - Consistent record of shipping customer-facing ML/AI and LLM features end-to-end. - Hands-on with NLP, RAG, time series, recommenders, anomaly detection and deep learning/transformers. - Strong Python skills, with production experience in ML frameworks and LLM tooling (HF Transformers, LangChain/LangGraph). - Cloud-ready, with experience across AWS services including Bedrock, S3, SageMaker, ECS and Lambda. - Experimentation-first approach: offline metrics, A/B tests, calibration/drift, human-in-the-loop, and telemetry tied to real outcomes. - Solid data engineering foundation: SQL, NoSQL/vector stores, streaming, data quality/governance, and collaborating on data contracts/observability. - Strong grounding in security, privacy and compliance, with a passion for Responsible AI principles.
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