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 Machine Learning Engineer

Payrails · Berlin

About Payrails


Payrails is a global payment software company helping leading enterprises to take control of their payment operations and maximize performance. With deep experience in the payments space and firsthand knowledge of merchants' challenges, we’ve seen how fragmented, complex, and inefficient these systems can become. Now, we are setting a new industry standard for how enterprises around the world manage and optimize payments, with more control, visibility and flexibility than ever before.

Our vision is to reimagine payments from the ground up. We are building a deeply integrated meta layer that spans the entire payment lifecycle with a modular architecture. This helps us give leading brands building blocks to craft solutions to most complex operational challenges, tailor seamless customer experiences and grow their business.

We are backed by some of the world’s top investors including Andreessen Horowitz, HV Capital, EQT Ventures and General Catalyst, who share our mission to simplify payment complexity globally.

At Payrails, we’re committed to building a team of exceptional people - not just talented, but driven to build, solve, and deliver at the highest level. Excellence isn’t just a value here; it’s a way of working. We believe that great people thrive in environments where there’s trust, clarity, and shared purpose. We work openly and collaboratively, with deep respect for each other’s craft. Everyone is encouraged to understand the bigger picture - what we’re building, why it matters, and what stands in the way. When people have that context, they move faster, take ownership, and make better decisions. We care about creating a culture where people feel inspired to do their best work and a deep sense of responsibility to help us bring our vision to life. Success at Payrails means staying focused on the problems that matter most, and executing with purpose.


Your team

At Payrails, data is at the core of everything we do. We don’t just analyze data; we turn it into actionable insights that fuel smarter decision-making and drive the future of our products. As we continue to revolutionize the payments industry we are seeking an exceptional Senior Data Engineer to help us in our mission.

Our Data Team is at the forefront of driving transformation, empowering every department to unlock the full potential of data

How you will make an impact

  • Design, build, test, and deploy robust machine learning models that power critical business decisions.

  • Develop and maintain scalable pipelines to support both model training and real-time inference.

  • Collaborate with data scientists, software engineers, and product teams to transform innovative ideas into production-grade solutions.

  • Implement industry best practices to ensure model reliability, scalability, and continuous performance improvement.

  • Stay abreast of the latest advancements in machine learning and AI, and integrate new techniques to keep our solutions at the cutting edge.

What we are looking for

  • You have extensive experience developing, deploying, and maintaining machine learning models in production environments.

  • You’re proficient in Python and experienced with ML frameworks such as TensorFlow, PyTorch, or similar.

  • You possess a strong background in data processing and analysis, using tools like Pandas, NumPy, Apache Spark or similar.

  • You have experience with orchestration technologies such as Airflow, Kubeflow, Flyte or similar.

  • You’re well-versed in AWS cloud and have hands-on experience with containerization and orchestration tools (i.e., Docker, Kubernetes).

  • You have a solid understanding of core ML concepts, including model evaluation, monitoring, and optimization.

  • You thrive in agile, collaborative settings and communicate complex technical concepts with clarity.

  • Experience with MLOps best-practices and infrastructure-as-code (such as Terraform) are a plus.

  • Experience with AWS Sagemaker is a plus.

  • Experience deploying and running models in low-latency production environments is a plus.

What we offer

  • High impact and high velocity environment with the most talented and ambitious people you will ever work with

  • A chance to shape the story of a company and a category from the ground up

  • Real ownership. You’ll have the freedom and trust to build, test, and take lead

  • A product used by the best brands around the world

  • Visa and relocation support for you and your family where required

  • Hybrid working with an office in the heart of Berlin

  • Regular team events, activities and off-sites

  • Discounted Urban Sports Club membership

  • Competitive salary and equity package

  • 27 days of annual paid vacation