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 .

Research Intern, Computational

Profluent · Emeryville, California, United States; Remote

Profluent is an AI-first protein design company. Founded in 2022, we develop deep generative models to design and validate novel, functional proteins to revolutionize biomedicine. Based in Emeryville, CA, we are backed by leading investors including Altimeter Capital, Bezos Expeditions, Spark Capital, Insight Partners, Air Street Capital, AIX Ventures, and Convergent Ventures, and have raised over $150M to date.

Our generative models learn the blueprint of life by modeling large-scale evolutionary data, enabling us to engineer and write biology in unprecedented ways. We are seeking a passionate Computational Research Intern to join moonshot projects at the intersection of bioinformatics and machine learning.

This is a rare opportunity to tackle open-ended scientific and engineering challenges with direct potential for high-impact publications and real-world applications in synthetic biology and protein engineering.

Responsibilities

  • Design and implement computational approaches to advance cutting-edge research in bioinformatics and machine learning
  • Analyze large-scale genomic and protein datasets to uncover new biological insights and capabilities
  • Collaborate closely with scientists and engineers across machine learning, protein engineering, and biology teams
  • Document and present research findings internally, with the potential to publish in leading journals and conferences

Qualifications

  • Enrolled in a BS, MS, or PhD program in Bioinformatics, Computational Biology, Computer Science, Statistics, or a related quantitative field
  • Strong programming skills in Python and familiarity with scientific computing libraries (e.g., NumPy, pandas, Jupyter)
  • Experience in one or more of the following: machine learning, large-scale data analysis, genomics, or protein bioinformatics
  • Excellent problem-solving skills, scientific curiosity, and ability to work both independently and collaboratively

Internship Details

  • Typical duration: 12 weeks, with flexible start dates
  • Hybrid: 2–3 days on-site per week in our Emeryville, CA headquarters
  • Salary: $1,667 per week
  • Opportunity to publish your work and make a lasting impact in computational biology and AI-driven protein design

What We Offer at Profluent

  • Work on moonshot projects at the frontier of AI and biology
  • Mentorship from leading experts in bioinformatics, machine learning, and synthetic biology
  • A dynamic, mission-driven environment with the resources of a fast-growing, well-funded startup
  • Competitive internship compensation and benefits