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 .

Engineering Manager - Search & Discovery

Vestiairecollective · Berlin

Vestiaire Collective is the leading global online marketplace for desirable pre-loved fashion. Our mission is to transform the fashion industry for a more sustainable future by empowering our community to promote the circular fashion movement. Vestiaire was founded in 2009 and is headquartered in Paris with offices in London, Berlin, New York, Singapore, Ho Chi Minh, and warehouses in Tourcoing (France), Crawley (UK), Hong Kong and New York.

We currently have a diverse global team of 600 employees representing more than 50 nationalities. Our values are Activism, Transparency, Dedication and Greatness and Collective.

The role
Vestiaire Collective is looking for a Berlin-based Engineering Manager to lead our cross-hub Discovery team across Berlin and Paris.

The Discovery team plays a critical role in how buyers explore, discover and engage with our catalog. The team owns key user-facing surfaces such as search, browsing, merchandising exposure, and content-driven discovery, with the objective of helping buyers find the right items at the right time while balancing business, operational and brand considerations.

As an Engineering Manager, you will lead a cross-functional squad of frontend and backend engineers to execute the Discovery roadmap end-to-end. You will work closely with Product, Design, Marketing, Merchandising and Data to deliver impactful features that improve user engagement, performance and scalability. Because our Discovery experience is heavily driven by search ranking and personalization algorithms, your squad will also actively integrate and rely on solutions built by our Data Scientists.

Reporting to the Director of Data Science and Engineering, you will combine people leadership, delivery ownership and technical contribution, while growing a strong, autonomous and product-oriented engineering team.

What you’ll do
- Lead the end-to-end execution of the technical roadmap, delivering high-quality, scalable Discovery features. 
- Collaborate with cross-functional partners (Product, Design, Marketing, Merchandising, CRM, Data) to align business priorities, user value, and technical feasibility. 
- Bridge the gap between software engineering and data science by guiding your backend engineers in applying Machine Learning Engineering practices to deploy and scale ML models in production.
- Manage and mentor a cross-functional squad of 6+ engineers. You will drive their professional growth through tailored coaching, impactful 1:1s, and clear career development plans, ensuring every specialist feels supported within a unified team culture.
- Actively contribute to technical discussions, system design and architectural decisions.
- Drive operational excellence and foster a healthy engineering culture by championing automation, code quality, observability, and continuous improvement.

Who you are
- 5+ years of experience as a software engineer (backend, frontend or full stack), and 3+ years in a hands-on management or technical leadership role.
- You have a proven track record of building high-traffic, user-facing products. You are comfortable designing distributed systems and managing real-time data pipelines that power search and recommendation engines.
- Proven track record of hiring, retaining and mentoring senior engineers, and building high-performing teams.
- Strong communication skills, with the ability to navigate ambiguity and align cross-functional stakeholders (technical and non-technical) around shared company goals.

Bonus: 
- Prior experience scaling E-commerce or Marketplace platforms
- Prior exposure to Machine Learning Engineering (MLOps) and collaborating closely with Data Scientists to integrate ML solutions into production.

Our tech stack
Languages: Golang, Python, TypeScript, Swift, Kotlin
Data & Infrastructure: OpenSearch, Kafka, Redis, Airflow, MariaDB  AWS, Kubernetes, Terraform, Ansible
Data & Analytics: Snowflake, Snowplow, Tableau
Tooling: Github, Jira, OpenAPI
The role
Vestiaire Collective is looking for a Berlin-based Engineering Manager to lead our cross-hub Discovery team across Berlin and Paris.

The Discovery team plays a critical role in how buyers explore, discover and engage with our catalog. The team owns key user-facing surfaces such as search, browsing, merchandising exposure, and content-driven discovery, with the objective of helping buyers find the right items at the right time while balancing business, operational and brand considerations.

As an Engineering Manager, you will lead a cross-functional squad of frontend and backend engineers to execute the Discovery roadmap end-to-end. You will work closely with Product, Design, Marketing, Merchandising and Data to deliver impactful features that improve user engagement, performance and scalability. Because our Discovery experience is heavily driven by search ranking and personalization algorithms, your squad will also actively integrate and rely on solutions built by our Data Scientists.

Reporting to the Director of Data Science and Engineering, you will combine people leadership, delivery ownership and technical contribution, while growing a strong, autonomous and product-oriented engineering team.

What you’ll do
- Lead the end-to-end execution of the technical roadmap, delivering high-quality, scalable Discovery features. 
- Collaborate with cross-functional partners (Product, Design, Marketing, Merchandising, CRM, Data) to align business priorities, user value, and technical feasibility. 
- Bridge the gap between software engineering and data science by guiding your backend engineers in applying Machine Learning Engineering practices to deploy and scale ML models in production.
- Manage and mentor a cross-functional squad of 6+ engineers. You will drive their professional growth through tailored coaching, impactful 1:1s, and clear career development plans, ensuring every specialist feels supported within a unified team culture.
- Actively contribute to technical discussions, system design and architectural decisions.
- Drive operational excellence and foster a healthy engineering culture by championing automation, code quality, observability, and continuous improvement.

Who you are
- 5+ years of experience as a software engineer (backend, frontend or full stack), and 3+ years in a hands-on management or technical leadership role.
- You have a proven track record of building high-traffic, user-facing products. You are comfortable designing distributed systems and managing real-time data pipelines that power search and recommendation engines.
- Proven track record of hiring, retaining and mentoring senior engineers, and building high-performing teams.
- Strong communication skills, with the ability to navigate ambiguity and align cross-functional stakeholders (technical and non-technical) around shared company goals.

Bonus: 
- Prior experience scaling E-commerce or Marketplace platforms
- Prior exposure to Machine Learning Engineering (MLOps) and collaborating closely with Data Scientists to integrate ML solutions into production.

Our tech stack
Languages: Golang, Python, TypeScript, Swift, Kotlin
Data & Infrastructure: OpenSearch, Kafka, Redis, Airflow, MariaDB  AWS, Kubernetes, Terraform, Ansible
Data & Analytics: Snowflake, Snowplow, Tableau
Tooling: Github, Jira, OpenAPI
What we offer 🎁

A meaningful job with an impact on the way people consume fashion and promote sustainability
The opportunity to do career-defining work in a fast-growing French-born scale up
The possibility to work as part of a globally diverse team with more than 50 nationalities 
Two days to help Project - reinforcing your activist journey and volunteer for an association
Significant investment in your learning and growth
Competitive compensation and benefits package (i.e 28 days of paid time off)

Research indicates that people from underrepresented backgroundsincluding women, people with disabilities, and other marginalized communitiesoften hesitate to apply for roles unless they meet every single requirement.

At Vestiaire Collective, we believe that talent comes in many forms, and we're committed to creating an inclusive environment where everyone can thrive. Your unique perspective could be exactly what our team needs, so we encourage you to apply even if you don't tick every box.

Vestiaire Collective is an equal opportunities employer  

Beware of Scams
Vestiaire Collective only contacts candidates via official emails ending in @vestiairecollective.com or [email protected] . We never use WhatsApp, Telegram, or similar apps for job offers, nor will we ever request payments or banking details.
If you receive a suspicious message, please report it to [email protected]