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 .

Principal Scientist, Cancer Biology

Generalproximity · San Francisco, CA

tl;dr

General Proximity is a seed-stage startup developing the next generation of induced proximity medicines (IPMs). Our OmniTAC drug discovery engine furnishes molecules that co-opt existing cellular machinery to overcome therapeutic challenges, which have remained unapproachable to other modalities for decades.

We are seeking a first-rate cancer biologist to help us pioneer this uncharted frontier of drug discovery.

Our Story

A long-standing challenge in drug discovery is the development of molecules capable of modulating difficult or "undruggable" targets. Disease-causing proteins can be dysfunctional in many different ways, but our armamentarium for fixing them is quite limited. The most common mechanism of action for FDA-approved drugs is inhibition[1], but there are many other possible perturbation types whose potential remains unrealized.

General Proximity is a seed-stage drug discovery company developing a novel platform technology to solve this problem. We make bifunctional drugs that induce the modification of drug targets by existing cellular machinery (rather than through direct modulation by the drug, the classical approach).

Historically, the development of technologies that allow one to push new buttons in biology has been an incredibly fertile field for the discovery of new medicines[2, 3, 4], and our technology holds the same promise.

 

The Position

We are seeking an experienced cancer biologist to help lead our Biology Team. In this position, you will help lead and manage our Biology Team and work closely with our Platform Team in the development of our core drug discovery technology.  

Your responsibilities will include phenotypic assay development, establishing pre-clinical in vitro/in vivo studies, performing mechanistic studies on lead drug molecules, spearheading forays into new oncology indications, and grant writing. 

 

About You

High Agency. Initiative, independence, and self-accountability are some of our most valued traits.

Enthusiastic. We love people who are excited about what they are doing and are generally attempting to build a high-energy team.

Intensity and Grit. Early-stage startups are hard. Drug discovery is doubly so. We are looking for candidates who have a demonstrated ability to stick with complex problems for the long haul, with a team that has your back along the way.

Prosocial. We are here to create life-saving medicines for the patients who need it most. You should be, too.

 

Qualifications & Nice-To-Haves

  • PhD in Cancer Biology, Cell Biology, or related field.  
  • 5-7+ years of industry experience.
  • Deep understanding of small-molecule drug discovery and its relationship to human disease.
  • Exceptional leadership, interpersonal, and communication skills, with a track record of managing high-performing, multidisciplinary teams.

  • Strong experience with:
    • Cellular and molecular biology, including cancer cell line work and associated assays, stable cell line generation (lentiviral and CRISPR-based systems), co-IP/pull-down assays, RNA-seq, global proteomics, flow cytometry, plasmid design/cloning etc.
    • Pre-clinical characterization and mechanistic elucidation of small-molecule drug candidates
    • Mechanistic studies of cancer cell signaling and PTM analysis
    • Phenotypic assay development for cancer drug discovery (low to high throughput)
    • Small molecule drug development campaigns (hit discovery, hit validation, dose-response studies, SAR and MOA studies)
  • Proficiency in:  
    • Managing a team of exceptional scientists and research associates 
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