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 .

Senior Research Engineer

Flow Traders · Hong Kong

Christy Wong Recruiter Hong Kong +852 2593 3050 [email protected] 2026-02-01 Technology

Flow Traders is looking for a Senior Research Engineer to join our Hong Kong office. This is a unique opportunity to join a leading proprietary trading firm with an entrepreneurial and innovative culture at the heart of its business. We value quick-witted, creative minds and challenge them to make full use of their capacities. 

As a Senior Research Engineer, you will be responsible for helping to lead the development of our trading model research framework and using it to conduct research to develop models for trading in production. You'll expand the framework to become global standard way of training, consuming, combining, and transforming any data source in a data-driven systematic way. You will then partner with Quantitative Researchers to build the trading models themselves.

What You Will Do

  • Help to lead the development and global rollout of our research framework for defining and training models through various optimization procedures (supervised learning, backtesting etc.), as well as its integration with our platform for deploying and running those models in production
  • Partner with Quantitative Researchers to conduct research: test hypotheses and tune/develop data-driven systematic trading strategies and alpha signals

What You Need to Succeed

  • Advanced degree (Master's or PhD) in Machine Learning, Statistics, Physics, Computer Science or similar
  • 8+ years of hands-on experience MLOps, Research Engineering, or ML Research
  • A strong background in mathematics and statistics
  • Strong proficiency in programming languages such as Python, with experience in libraries like numpy, pytorch, polars, pandas, and ray.
  • Demonstrated experience in designing and implementing end-to-end machine learning pipelines, including data preprocessing, model training, deployment, and monitoring
  • Understanding of and experience with modern software development practices and tools (e.g. Agile, version control, automated testing, CI/CD, observability)
  • Understanding of cloud platforms (e. g., AWS, Azure, GCP) and containerization technologies (e. g., Docker, Kubernetes)

Flow Traders does not accept unsolicited resumes from any professional staffing or search firms. All resumes, and any other information identifying potential candidates, submitted to any employee at Flow Traders via-email, the Internet or directly without a valid and signed search agreement will be deemed free to contact by Flow Traders without any restrictions and no placement fee of any kind will be paid in the event the candidate is hired by Flow Traders.