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 .

Head of Fraud

Comun · NYC Office

About Común

Comun’s mission is to help Hispanic immigrants turn their hard work into upward mobility — starting with financial services that support their transition from a cash-based system to the digital economy.

We offer checking accounts that can be opened using 100+ types of Latin American IDs, access to over 90K locations nationwide to deposit cash, international transfers to 17 countries at market-leading rates, and 24/7 bilingual customer support with <5 min SLA across email, chat, and phone.

We currently process over $1.5B in annual transaction volume and surpassed $100M in annualized international transfers just six months after launch. Comun has raised +$50M from top investors including Redpoint, Costanoa Ventures, and South Park Commons. Our team brings experience from leading fintech companies like Brex, Nubank, and Mercury.

We believe immigrants are the ultimate entrepreneurs — driven by relentless ambition and a vision for a better future for their families. Comun exists to serve them throughout their journey.

Learn more at comun.app/nosotros

Article here

About the role

The Head of Fraud will be in charge of seeding the risk function at Común, ensuring that we can accomplish our mission of providing financial access to immigrants while removing bad actors from our systems. This is a highly collaborative role that will interface with most company functions and touch our entire product suite, and is a key dependency to enable a great customer experience.

We are looking for someone with a strong analytical background who can get their hands dirty with data analysis and modeling and can succeed with a lean team. This role will own all of KYC, ongoing monitoring, fraud exposure, and anti-money laundering, and report directly to the founders.

What you’ll do:

  • Reporting directly to the founders you'll collaborate with Growth, Compliance, Operations, Product, Engineering, and our partner banks to iterate on a KYC policy that is inclusive, compliant, and continuously filtering out bad actors.

  • Maintain a strong monitoring practice across both automated alerts and BPO manual reviews, to enable sharp decision-making and provide continuous feedback to our automated models.

  • You will own fraud exposure, and will work on data models to continuously eradicate fraud losses across our features: check deposits, ACH transfers, debit card disputes, and peer transfer chargebacks.

  • Own and continuously optimize our real-time transaction authorization model for remittances and P2P.

  • Work with Compliance and Data to maintain tight anti-money laundering controls across any new addition to our feature set.

  • Own a holistic customer risk model that draws from behaviors across our entire feature set to determine what experience we can show to each user.

  • Improve and maintain our fraud stack, ensuring we have the best tools and vendors to make data-driven decisions.

  • Collaborate with Product and Engineering to establish robust controls across our product suite and establish the appropriate testing frameworks to ensure we achieve the intended outcomes.

What you’ll bring

  • Experience combating coordinated fraud attacks and knowledge of best practices for fraud mitigation on both the merchant and issuing side.

  • Hands-on experience with SQL, machine learning, regressions, and data modeling.

  • Experience building holistic customer risk models in other fintech products

  • Familiarity with money laundering patterns, behaviors, and mitigation strategies.

  • Familiarity with fraud, KYC, and risk vendors across orchestration, data, and decisioning needs.

  • A high degree of collaboration across many stakeholders at Común’s leadership level.

  • A customer-obsession mindset that allows you to properly set tradeoffs between stricter controls and providing a delightful customer experience.

    Requirements

  • 5-8 years of experience in risk or fraud functions across fintech companies

  • Experience in a fast-growing startup

  • Living in or willing to relocate to New York

  • An interest in serving an underserved community :)

Team

We are a team of 40 based out of New York, coming from industry-leading companies like Brex, Nubank, Cruise, and Verkada. Over half of us are immigrants, and have experienced the problems we’re solving first hand. We value customer focus, high ambition, principled decision-making, and deep trust.

Full Time Employee Benefits

  • Competitive salary and generous equity

  • Medical, dental, and vision insurance

  • Gym Pass subscription

  • Daily office lunch in NYC Office

  • Paid parental leave

  • Flexible PTO

  • Remote-friendly when traveling

  • Company-wide offsites

  • 401(k) for US employees

  • Visit to our NYC Office for remote team members

  • Visa sponsorship if applicable

Común is proud to be an equal opportunity employer. We are committed to building a diverse and inclusive culture that celebrates authenticity. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics.