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 .

Applied ML Scientist

Pdtpartners · New York, NY

PDT, a quantitative investment manager, is hiring problem solvers who blend programming and applied research experience. Individuals in this role will devise, implement, evaluate, and iterate to create and improve statistical methods vetting them through direct application to enhancing our trading strategies. Applied ML scientists are expected to navigate quantitative and technical challenges within a project to advance our research methodology. They will have ample opportunity to collaborate with our deep bench of senior researchers and technologists.

PDTers are creative, energetic, friendly, entrepreneurial, and collaborative. If you could walk around our office, you’d see that we’re a focused, intent, and nimble company with none of the attitude and bureaucracy of a stereotypical Wall Street trading firm. We love to work on challenging and complicated problems, that in return give a chance to make outsized, direct impact on our bottom line. For the right talent, there is fantastic growth potential.

This is a hybrid position and will require the person to work from our New York City office at minimum 3 days a week. 

Why join us? 

PDT Partners has a 30+ year track record and a reputation for excellence. Our goal is to be the best quantitative investment manager in the world—measured by the quality of our products, not their size. PDT’s very high employee-retention rate speaks for itself. Our people are intellectually extraordinary and our community is close-knit, down-to-earth, and diverse. 

Responsibilities:

  • Work closely with senior researchers on a variety of trading strategies and research projects, with the opportunity to conduct independent research and originate research topics over time
  • Contribute to the long-term success of our research-driven algorithmic trading business

Below is a list of skills and experiences we think are relevant. Even if you don’t think you’re a perfect match, we still encourage you to apply because we are committed to developing our people

  • Solid mathematical and analytical ability; exceptional problem-solving and modeling ability
  • Research intuition
  • Experience in programming (Python, R, Matlab, C++)
  • Excellent communication and collaborative white board skills
  • Meticulous and detail-oriented, and innately driven to understand issues deeply
  • Experience with/interested in working with large data sets
  • Self-motivated and highly-productive, with a strong sense of ownership and urgency
  • Able to work collaboratively and productively with others
  • Enjoy solving complex, difficult, real-world problems
  • Entrepreneurial and creative  
  • Finance knowledge is not required or expected
  • PhD preferred 
  • Undergraduate or Masters degree with equivalent industry experience in machine learning 
    • 2+ years of applied machine learning research experience
  • Strong publication record
  • Experience with the Python scientific stack

The salary range for this role is between $190,000 and $250,000. This range is not inclusive of any potential bonus amounts.  Factors that may impact the agreed upon salary within the range for a particular candidate include years of experience, level of education obtained, skill set, and other external factors.

PRIVACY STATEMENT: For information on ways PDT may collect, use, and process your personal information, please see PDT’s privacy notices.