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 Scientist

Rolls-Royce · Pune

Key Accountabilities:
  • Develop new Algorithms that involve descriptive, prescriptive, predictive analytics, advanced statistics, and big Data.
  • Continuously bring in the knowledge of latest techniques and methodologies in Data analytics, Machine Learning and Statistics.
  • Understand complex problem statements and break-down into manageable tasks / work-packages. Strong familiarity with Agile frameworks.
  • Create data visualization to provide analytical insights.
  • Collaborate with several subject matter experts in the organization for deployment and validation of algorithms on existing products.
  • Work with software engineering best practices such as version control, continuous integration, test driven development.
  • Strong rigor in automating repetitive tasks.
  • Define work packages for external partners for analytics task and steer the development by meeting quality requirements along with timeline.
  • Lead and provide technical guidance to a team of data analysts and programmers to derive actionable insights from structured / unstructured data.
  • Ensure quality of data and solution developed. Create high quality documentation of developed solutions.
Qualifications
  • Minimum Bachelors / Masters in Engineering with 6-10 years of relevant experience.
  • Strong domain knowledge about internal combustion engine and associated subsystems.
  • Previous experience with creating functions and algorithms to support internal / external customers within an engine development or service based environment.
  • Should be able to identify opportunities for monetizing test bench and service data.
  • Business acumen and strategic inclination to help leadership take data driven decisions. Ability to create business proposals.
  • Strong Programming background and expertise in building machine learning models using Matlab/python or any other programming language.
  • Machine Learning good knowledge of machine learning methods like k-Nearest Neighbors, Naive Bayes, SVM, Decision Forests.
  • Experience with Data Visualization Tools like matplotlib, ggplot, d3.js., Tableau
  • Excellent Communication Skills, Stakeholder management
  • Ability to formulate multiple complex problems into hypothesis and proof of concepts for testing.
  • Should have experience in regression analysis and time series data.
  • Able to work in Scrum methodology and Agile framework.
  • Strong analytical skills to identify problems in data and propose solutions.
  • Ability to transform business requirements into data science formulations and implement sustainable and scalable solutions.
  • Attention to detail and strong data orientation.
  • Ability to work in global cross functional teams.
  • German language is an added advantage.