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 .

Quantitative Trader – Equities (Strategy Monetization)

Imc · Hong Kong, Hong Kong; Sydney, Australia

IMC is hiring a Quantitative Trader to focus on monetization research and back testing for high- to mid-frequency delta-one equity strategies. This role emphasizes research depth, systematic evaluation, and capital efficiency, partnering closely with quant researchers and engineers to turn signals into scalable, profitable trading strategies.

Based in Sydney, this role is ideal for candidates who excel at research-driven trading problems, large-scale data analysis, and rigorous performance validation. For exceptional candidates from top global trading firms, Hong Kong location may be considered.

Core Responsibilities

  • Research and evaluate new trading signals and strategy ideas with a focus on monetization potential
  • Design and run large-scale back tests to assess PnL, risk, capacity, and robustness
  • Analyse transaction costs, market impact, and execution assumptions within back testing frameworks
  • Optimize portfolio construction, capital allocation, and risk controls across strategies
  • Work with engineers to improve back testing infrastructure, data quality, and research tooling
  • Partner with live traders to ensure research assumptions align with real-world execution behaviour
  • Drive strategies from research validation through production readiness

Skills & Experience

  • Degree in a quantitative field (Mathematics, Physics, Computer Science, Engineering, Economics, or similar)
  • 3+ years of experience in quantitative trading or monetization research, preferably in equities
  • Strong experience with back testing frameworks, large datasets, and systematic performance evaluation
  • Deep understanding of market microstructure, transaction costs, and scalability constraints
  • Strong programming skills (Python/C++ strongly preferred); ability to write clean, research-grade code
  • Rigorous, detail-oriented mindset with strong statistical intuition
  • Experience at leading systematic or proprietary trading firms is a strong plus

About Us

IMC is a global trading firm powered by a cutting-edge research environment and a world-class technology backbone. Since 1989, we’ve been a stabilizing force in financial markets, providing essential liquidity upon which market participants depend. Across our offices in the US, Europe, Asia Pacific, and India, our talented quant researchers, engineers, traders, and business operations professionals are united by our uniquely collaborative, high-performance culture, and our commitment to giving back. From entering dynamic new markets to embracing disruptive technologies, and from developing an innovative research environment to diversifying our trading strategies, we dare to continuously innovate and collaborate to succeed.