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 .

AI Financial Modeling Extern

F2 Ai · San Francisco

AI Financial Modeling Extern — F2 AI

Location: San Francisco, CA / In-Person or Remote

Commitment: 5+ hours per week | 4 - 12+ weeks

Compensation: $50/hr

About F2

F2 is the AI platform for private markets investors — purpose-built to transform how institutional teams underwrite, diligence, and deploy capital. Our AI converts messy, unstructured deal materials into investment-grade insights in minutes, helping private credit funds, commercial banks, and private equity firms make faster, more confident decisions. Backed by leading investors, including NFX and Y Combinator, we’re scaling a world-class product and engineering team to build the future of vertical AI for finance.

Role Overview

We are seeking 1–2 high-performing externs from top-tier Investment Banking or Private Equity backgrounds to help architect AI-native financial modeling on the F2 platform.

You will work directly with the EPD and Sales team in our SF office to translate institutional-grade financial modeling standards into agentic, automated workflows. This is a hands-on opportunity to help define how AI should build and reason through financial models.

What You’ll Do

  • Teach F2 agent best practices across financial models

  • Design and standardize financial modeling templates optimized for AI execution with first principles approach

  • Define formatting, structure, and best practices consistent with institutional modeling standards

  • Perform high-rigor QA on AI outputs to ensure investor-grade precision

  • Pressure-test edge cases and help identify failure modes in automated modeling workflows

You Might Be a Great Fit If

  • You have prior experience in Investment Banking, Private Credit, or Private Equity with heavy financial modeling exposure

  • You’ve built and audited complex 3-statement, LBO, or credit models from scratch

  • You have strong instincts for model hygiene, structure, and institutional formatting standards

  • You think critically about model logic and enjoy breaking / stress-testing systems

  • You’re excited about applying AI to transform financial workflows

Preferred Qualifications

  • Experience in investment banking, private credit or private equity.

  • Exposure to model auditing, QA processes, or financial modeling best-practice frameworks.

Why F2?

  • Join a fast-growing AI startup reshaping workflows in private markets and finance.

  • Be part of a small, high-impact team where your work directly influences product and company trajectory.

  • Competitive compensation with equity upside and benefits.

  • Collaborative, mission-driven culture that values craftsmanship, curiosity, and rapid iteration.