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 Data Engineer

Codat · Remote

About Codat

Codat is an advisory intelligence solution purpose-built for modern commercial banking. Through rich, specialized data, forward-looking insights, and integrated workflows, Codat empowers banking teams to deepen their relationships, grow their revenue, and simplify their day-to-day work.

Founded in 2017 and backed by JPMorgan, PayPal, Amex, Plaid, and Shopify, Codat has successfully powered over 350,000 connections to business customers’ financial systems — and is trusted by industry leaders to turn scattered information into actionable, strategic advantages in real time, every time.

The Role

We're looking for a Senior Data Engineer to join our Insights team. You'll be hands-on every day — writing production code, building and maintaining data pipelines, and shipping features that turn raw data into actionable intelligence for our clients. You'll work across the full project lifecycle, from understanding the problem through to delivery, and you'll care as much about code quality and operational reliability as you do about getting things shipped.

This isn't a platform architecture role. You'll be building and owning pipelines end-to-end, not designing abstractions for other engineers to build on. You'll thrive if you're motivated by solving real user problems and you want to work somewhere your code has direct, visible business impact.

What You'll Do

  • Write production code daily, most likely in Python, building and maintaining the data pipelines that power our Insights products.

  • Own the full lifecycle of your projects: understanding the data domain, designing pragmatic solutions, shipping them, and keeping them running reliably.

  • Drive technical quality through strong engineering practices — testing, observability, data quality checks, and clean, maintainable code.

  • Collaborate with product, data science, and engineering stakeholders to shape what we build and how we build it.

  • Identify opportunities to apply AI within our products and workflows where it delivers genuine value.

  • Contribute to the growth of the team by sharing knowledge and championing good engineering practices.

What You'll Bring

  • Strong software engineering fundamentals: you write well-tested, production-ready code and care about maintainability, observability, and operational excellence.

  • Solid experience with modern data engineering tools and patterns — some combination of SQL, Spark, Databricks/Delta Lake, orchestration tools (Dagster, Airflow, Temporal), and DBT.

  • Proficiency in a strongly typed language, ideally Python or C#.

  • Comfort with modern deployment practices: CI/CD, containerisation (Docker), and cloud-based infrastructure.

  • A product mindset — you want to understand the business domain and use that understanding to influence what you build, not just how you build it.

  • The ability to communicate clearly with both technical and non-technical colleagues.