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 .

Computer Vision/Machine Learning Intern

Scandit · Zurich

Scandit gives people superpowers. Whether enabling delivery drivers to make quicker deliveries, matching a patient with their medication, or allowing retailers to make store operations more efficient, our technology automates workflows. It provides actionable insights to help businesses in a variety of industries. Join us as we continue to expand, grow, innovate, and help take Scandit to the next level.

About the Internship

We are looking for students with a passion for computer vision or machine learning to join one of the teams in Zürich for four to six months. You will be a part of product development and you will help us improve and extend algorithms and their automated testing infrastructure.

Scandit offers an excellent opportunity to apply the theory from your studies while gaining hands-on experience with industry best practices in a international team.

What You Will Do

We have many interesting projects to offer. Depending on your background and interests, you could work on one of the following projects:

  • Improve barcode scanning algorithms in difficult scenarios such as surfaces with deformations, glare or reflections
  • Enhance the real-time visual tracking and pose estimation system of our solutions through the integration of additional sensor measurements and cutting-edge machine learning algorithms
  • Enhance our object and context detection systems by developing, refining, and integrating state-of-the-art machine learning algorithms tailored to our specific domain
  • Enhance our real-time visualization system to analyze and develop our computer vision algorithms
  • Reduce manual steps in our image annotation tools with smart algorithms
  • Develop image classification, matching and/or reconstruction features in order to improve the algorithms for understanding the current state of shelves and products in supermarkets

Our Tech Stack

  • Computer vision algorithms: C++17, CMake
  • Machine learning training and tooling, cloud processing: Python, Pytorch
  • Acceleration: SIMD, Vulkan, CoreML

Who You Are

  • Highly motivated student, interested in an internship of four months or longer
  • Enrolled in or completed a bachelor’s or master’s program in computer science, information technology, robotics or a related field
  • Solid knowledge of data structures and experience in object-oriented programming
  • You have taken courses in computer vision, image processing and/or machine learning
  • Ideally you already had some exposure to solving a computer vision problem in a semester project or thesis
  • If you are interested in working on the core image recognition algorithms, solid C++ programming skills will be needed
  • Python programming knowledge is a plus

What We Offer

  • We are certified as a “Great Place to Work” in 7 countries!
  • A highly skilled team and a fun environment where you can put your enthusiasm for computer vision challenges and cutting-edge technologies to use
  • Hackathons, summer parties, company outings and other regular events
  • Office in the city of Zürich (Hardbrücke)

Imagine the What. Build the How.

At Scandit we strive to create an inclusive environment that empowers our employees. We believe that our products and services benefit from our diverse backgrounds and experiences and are proud to be a safe space for all.

All qualified applications will receive consideration for employment without regard to race, colour, nationality, religion, sexual orientation, gender, gender identity, age, physical [dis]ability or length of time spent unemployed. 

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