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 .

Data Quality Analyst

Octus · London, England, United Kingdom

Octus

Octus is a leading global provider of credit intelligence, data, and analytics. Since 2013, tens of thousands of professionals across hedge fund, investment banking, management consulting, and law firm verticals have come to rely on Octus to make better, faster, and more confident decisions in pace with the fast-moving credit markets.
For more information, visit: https://octus.com/

Working at Octus

Octus hires growth-minded innovators and trailblazers across the globe to drive our business and culture. Our core values – Action Oriented, Customer First Mindset, Effective Team Players, and Driven to Excel – define an organizational ethos that’s as high-performing as it is human. Among other perks, Octus employees enjoy competitive health benefits, matched 401k and pension plans, PTO, generous parental leave, gym subsidies, educational reimbursements for career development, recognition programs, pet-friendly offices (US only), and much more. 

Role

We are seeking a Data Quality Analyst to help design and implement Octus’s first standardised data quality framework, ensuring consistency, reliability, and trust across all analytical and client-facing datasets. This role is highly hands-on and sits at the intersection of data quality, data operation, and data governance. You will partner closely with the data operation team, dataset owners and engineers to define quality standards, implement automated checks, and embed data quality into our modern data stack.

This is a game-changing opportunity to seize the reins and define the future of data integrity driving how data quality is not just measured, but aggressively enforced and scaled across the entire organisation.

This position is based in our London office, operating on a hybrid schedule (3 days in office per week).

Responsibilities

Data Quality Framework & Standards

  • Design and implement a scalable data quality framework covering accuracy, completeness, timeliness, and consistency across datasets
  • Define reusable data quality patterns and testing approaches aligned with business requirements
  • Help establish prescriptive standards for data modeling, transformations, and ingestion

Automation & Testing

  • Build and maintain automated data quality checks using SQL, dbt tests, and/or similar frameworks
  • Implement business rule validations, anomaly detection, and functional data tests
  • Embed quality checks directly into transformation pipelines and CI/CD workflows

Collaboration & Enablement

  • Partner with Dataset Owners to define dataset-specific quality expectations
  • Support adoption of data quality tooling, best practices, and documentation across teams
  • Act as a subject-matter expert for data quality within the data operations ecosystem

Monitoring, Incident Management & Reporting

  • Identify, triage, and help resolve data quality issues across pipelines and downstream consumers
  • Contribute to data quality monitoring dashboards and reporting
  • Support root-cause analysis and preventative improvements

Documentation

  • Document data quality standards, testing approaches, and framework usage
  • Contribute to internal enablement materials and best-practice guides

Requirements

  • Strong hands-on experience with SQL
  • Experience working with dbt or similar transformation/testing frameworks
  • Proficiency with Git and collaborative development workflows
  • Experience designing or implementing data quality checks, validations, or testing frameworks
  • Solid understanding of modern data warehouse concepts
  • Ability to work cross-functionally with technical and non-technical stakeholders
  • Must be legally authorized to work in the country where the position is located

Equal Employment Opportunity

Octus is committed to providing equal employment opportunities to all employees and applicants for employment without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, age, disability, genetic information, marital status, pregnancy, veteran status, or any other legally protected status. We strive to create an inclusive and diverse work environment where all individuals are valued, respected, and treated fairly. We believe that diversity enriches our workplace and enhances our ability to innovate and succeed.