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 Researcher

Engineersgate · New York, NY

About the Role

Engineers Gate (EG) is a leading quantitative investment company focused on computer-driven trading in global financial markets.  We are a team of researchers, engineers, and financial industry professionals using sophisticated statistical models to analyze data and identify predictive signals to generate superior investment returns. EG’s investment teams each focus on their independent strategies while utilizing the firm’s proprietary, state-of-the-art technology and data platform to optimize their alpha research.

We are seeking a highly motivated and experienced Quantitative Researcher to join one of our systematic equity trading teams. In this role, you will be able to leverage the team’s existing research and trading infrastructure to develop innovative systematic trading strategies in their full cycles, from deep data analysis to idea generation and backtesting, and ultimately strategy deployment. The ideal candidate will have strong programming skills and demonstrate a passion for diving deep into data analysis, allowing for creative alpha generation driven by both in-depth understanding of the data and financial intuition. As part of a small team, the Quantitative Researcher will report directly to the Portfolio Manager and will be tasked in all aspects of systematic trading, leading to tremendous growth opportunities for the successful candidate.

We place a high value on continuous learning and development and this role represents a unique opportunity to work alongside and learn from highly experienced team members.

Joining Engineers Gate offers a unique opportunity to work at the forefront of systematic trading, where innovation and quantitative analysis intersect. We are passionate about implementing scientific and mathematical methods to explore and solve problems in the global financial markets. If you thrive in a fast-paced, data-driven environment, we encourage you to apply.

Key Responsibilities

  • Process and analyze all kinds of data sets in various formats, structured or unstructured.
  • Collaborate closely with the PM to develop alpha signals out of both traditional and alternative data sets.
  • Adopt the data driven approach to come up with creative alpha generation ideas and rigorously backtest these ideas.
  • Collaborate with other team members to improve existing research and trading infrastructure, as well as adding new data analysis and research tools.
  • Take a proactive approach to problem-solving, demonstrating a high level of motivation and initiative in the pursuit of innovative trading strategies.
  • Stay informed about market trends, emerging technologies, and advancements in quantitative finance.

Required Skills, Qualifications and Experience

  • Familiar with alpha research methodologies in cash equities, developed and traded systematic equity strategies with proven track records.
  • A minimum of two years of alpha research experience in systematic equity trading, exceptional fresh graduate with advanced degrees in quantitative majors could be considered.
  • Very strong programming skills, preferably in Python.
  • Experience on building scalable time series data analysis infrastructure is a big plus.
  • Knowledge on portfolio construction and trade execution is highly desirable.
  • Ability to work both independently with light guidance and effectively collaborate with other team members when needed.

The salary for this role is anticipated to be between $130k and $150k.  This range does not include any potential bonus amounts, other forms of compensation, or benefits offered.  Actual compensation for successful candidates will be carefully determined based on a number of factors, including the candidate’s skills, qualifications, education and experience.

 

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