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 Staff Data Scientist, Quickbooks Mountain View, California

Intuit

Intuit QuickBooks is a market leader in accounting solutions for small and mid-market businesses. The Accounting Automation team within the Global Business Solutions Group (GBSG) is dedicated to delivering 'Done-for-you' accounting experiences using cutting-edge GenAI and Agentic solutions. This team recently launched Accounting Agent, an industry-leading AI-powered Agentic solution that automates bookkeeping and suggests transaction categorization, helping users stay organized and accurate. Building on this milestone, the team plans to launch several new cutting-edge solutions next year.

Our team's charter is to deliver delightful customer experiences and drive customer impact by developing insights, models, and strategic thought partnerships that assist small and mid-market business customers in managing their finances. We collaborate with Product Management, Commercial, Finance, Business Operations, Design, and Engineering teams to promote data-driven decisions through strategic thinking, data analysis, experimentation, and predictive analytics.

As a senior member of this team, accelerating growth for a strategic company priority, you will delve into our data to uncover actionable insights and provide recommendations that fuel the growth of this new product. The ideal candidate will possess a strong background in quantitative analysis using large datasets and a track record of driving influence and alignment with data.


Responsibilities

As a Senior Staff Data Scientist on the Product Data Science team, you will dive deep into our data to uncover actionable insights and shape strategic decisions. Your contributions will directly impact our product development and Go-to-Market (GTM) strategies. This role requires a strong background in quantitative analysis, data-driven decision-making, and expertise in working with large data sets.

  • Conceptualize business problems or opportunities, formulate hypotheses and goals, define key metrics, and make actionable recommendations.
  • Drive strategic insights that shape the future of Intuit's core Accounting offering, impacting millions of small businesses.
  • Develop predictive models, conduct experimentation beyond A/B testing, and generate actionable customer insights that inform product innovation.
  • Build and apply durable customer segmentation patterns to refine product targeting, positioning, and customer experience.
  • Partner closely with Product Management, Marketing, Engineering, Design, and Analytics leaders to deliver insights that drive product strategy and growth.
  • Translate complex data insights into actionable recommendations for technical and non-technical stakeholders and business leaders.

Qualifications

The ideal candidate is a curious, proactive data scientist with experience in building scalable solutions, a strong understanding of customer behavior, and a passion for accounting.

  • BS or MS degree in Statistics, Mathematics, Operations Research, Computer Science, Econometrics, or a related field.
  • 10+ years of experience in data science or product analytics, with a strong foundation in predictive modeling, customer segmentation, and experimentation.
  • Ability to formulate data-backed strategies that will drive step-function growth for the business and increase customer benefit.
  • Ability to generate hypotheses grounded in customer behavior, industry trends, and external market factors.
  • Experience in designing and interpreting complex experiments beyond traditional A/B testing methods.
  • Demonstrated experience in building reusable and scalable analytics solutions, with a focus on efficiency and avoiding duplication of work.
  • Outstanding communication skills with the ability to influence decision-makers and build consensus with teams.
  • Quick learner, adaptable, with the ability to work independently or as part of a team in a fast-paced environment.
  • Technical Skills: 

Technical Skills:

  • Advanced SQL skills and proficiency in visualization tools such as Qlik, Tableau, Plotly Dash.

  • Strong analytical and modeling skills using Python (for its rich suite of statistical and modeling libraries like NumPy, Pandas, Scikit-learn, etc.).

  • Experience with Causal inference techniques such as propensity score matching, difference-in-differences, and synthetic control methods.

  • Familiarity with Generative AI and other evolving technologies to accelerate insights from multi-modal data.


Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is: 

Bay Area California $ 204,500- 276,500