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 .

Data Scientist

Hoppr · Remote

Company Description:

HOPPR is at the forefront of innovation in medical imaging, developing the first multimodal AI foundation model. Our deep learning platform, unique for its proprietary privacy-compliant trust architecture, integrates diverse data sources with cutting-edge AI/ML development. HOPPR is co-founded by Dr. Khan Siddiqui, a visionary leader with a prolific background including founding higi, former roles at Hyperfine (NASDAQ:HYPR), and Microsoft.

Role Description:

Join HOPPR as a Data Scientist and play a pivotal role in shaping the future of multimodal AI in medicine. Collaborate with researchers, engineers, and clinicians to enhance data infrastructure and develop impactful solutions with vast amounts of unstructured datasets like radiology scans, patient reports, and electronic health records (EHRs). You’ll tackle complex challenges and drive innovations that transform patient care. 

Key Responsibilities:

  • Design and develop robust pipelines using advanced methods with large language models (LLMs) to extract features and label data from unstructured datasets 
  • Create and implement rigorous evaluation metrics to assess feature extraction processes, ensuring continuous improvement aligned with clinical and product goals. 
  • Enhance and maintain scalable, reproducible data science infrastructure to support agile development and secure operations across partitioned client environments. 
  • Design and implement MLOps practices to streamline, scale, and automate machine learning workflows. 
  • Manipulate, analyze, and manage large-scale datasets using Python, SQL, and other tools. 
  • Work closely with engineers, clinicians, and product teams to ensure data solutions are aligned with user needs and drive meaningful outcomes. 
  • Thrive in a dynamic and rewarding environment that emphasizes excellence, autonomy, and impact. 

 

Qualifications:

  • Master’s or PhD in Computer Science, Engineering, Data Science, or a related field. Senior and Principal roles considered based on experience.
  • 1+ years of professional data science experience, with a proven ability to train, evaluate, and deploy machine learning models, including large language models.
  • Proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow), as well as experience with data manipulation tools like SQL, pandas, or NumPy.
  • Familiarity with ML Ops practices and deploying models into production pipelines (preferred).
  • Knowledge of healthcare data, such as radiology images or EHRs, is a plus.
  • Strong ownership mindset, entrepreneurial spirit, and product-focused approach to solving impactful problems.

 What We Offer:

  • Competitive base salary + equity. 
  • A key role in a fast-growing startup with immense potential. 
  • Generous benefits: medical/dental/vision, 401k, PTO, and parental leave. 
  • Remote first with hybrid options available at our NYC and SF Bay Area offices. 
  • An innovative, collaborative, and supportive work environment. 
  • Incredible teammates who inspire growth and learning. 

 

HOPPR is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

Important Note: This opportunity is open exclusively to US citizens and permanent residents. We kindly request that recruiters and agencies refrain from contacting Dr. Khan Siddiqui or any HOPPR team members directly regarding this role. Unrequested outreach from recruiters will not be entertained or responded to. Thank you for respecting this directive and helping us maintain a focused and efficient hiring process.

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