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 .

Advanced Data Analytics Lead

Putnamassociatesllc · Boston, Massachusetts

Position Summary 

Come join a growth engine as a leader in our Data & AI Practice! Inizio Advisory & Putnam Associates continue to advance our Commercial Life Sciences Data, Analytics and AI Team and Solutions.  We are looking for an experienced innovator and senior leader to join Data Strategy, Analytics and AI Practice.   

The Advanced Data Analytics Lead role within the Data Strategy, Analytics and AI team will be responsible for advising clients on business strategy through data-driven decision-making, leading project teams, and developing innovative solutions to complex business challenges through data and AI. The ideal candidate should have a deep understanding of Pharmaceutical commercial business strategies, project management, and a proven problem-solving capability through data strategies, technology, and emerging AI/GenAI solutions.  

This leadership role is responsible for independently driving client and business development at the company.  They must effectively identify potential client engagements, qualify leads and drive the business development process.  They will write and submit project proposals, develop and deliver capability presentations, and respond to prospective client needs.  They are responsible for developing intellectual thought leadership for the company and for developing and enhancing practice areas within the firm.    

They are also responsible for building and enhancing existing Pharma client relationships and for overseeing the delivery of Data Strategy/Analytics/AI projects, managing a global team of data scientists and business analysts to support and deliver client projects.  

In addition to Putnam growth, this is a broader opportunity to support growth within the Inizio Advisory companies to collaborate and work with other teams, as the Data Analytics & Strategy practice evolves to support the industry and our clients’ needs.  

Holistic view of responsibilities and measurements of success:  

  • Extensive project work planning and client interaction and management.   
  • Leadership effectiveness through team management effectiveness, coaching and mentoring, participation in positive firm culture building, practice area development contributions, and general firm development contributions   
  • Development of key insights from all workstreams and translation of those insights into a compelling storyline and presentation   
  • Proposal development and revenue generation   
  • Participation in industry thought leadership  
  • Establish clearer resourcing method and process for the team for scale  
  • Support the evolution of our hiring strategy for team based on expected future client work (e.g. growth of claims analytics offerings, commercial analytics, AI/GenAI solutions, and other growth areas accordingly.  

  

Desired Skills & Experience   

  • Experience in Life Sciences data analytics (minimum of 10 years) and consulting  
  • Working knowledge of pharmaceutical data sets such as: claims data, prescription data, lab data, change/content data, engagement and experience data  
  • Experience in data visualization tools (e.g., Tableau, PowerBI, Qlik Sense)  
  • Experience in healthcare datasets (e.g., Komodo, IQVIA, Symphony, Truven, Optum, Flatiron, Charge Master, Lab, Provider and Payer data)