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 Analytics Engineer

Underdogfantasy · United States/Remote

At Underdog, we make sports more fun.

Our thesis is simple: build the best products and we’ll build the biggest company in the space, because there’s so much more to be built for sports fans. We’re just over five years in, and we’re one of the fastest-growing sports companies ever, most recently valued at $1.3B. And it’s still the early days.

We’ve built and scaled multiple games and products across fantasy sports, sports betting, and prediction markets, all united in one seamless, simple, easy to use, intuitive and fun app. 

Underdog isn’t for everyone. One of our core values is give a sh*t. The people who win here are the ones who care, push, and perform. If that’s you, come join us.

Winning as an Underdog is more fun.

At Underdog, data is at the core of every decision we make — from scaling our products to delighting our users. As a Senior Analytics Engineer, you’ll be a cornerstone of our data foundation. You won’t just be building pipelines; you’ll be architecting the models and metrics that power everything from executive dashboards to product experiments. This is a high-impact role where your work will directly influence business strategy, growth, and product innovation.

About the role

  • Build and maintain core dbt data models that turn raw data into clean, trusted, analysis-ready assets (e.g., User 360, Contest Fact, Marketing Attribution).
  • Implement and manage a semantic layer (dbt MetricFlow, Omni, or equivalent) to standardize definitions of key metrics across the company.
  • Own data quality and reliability, setting up automated testing, monitoring, and alerting frameworks.
  • Collaborate with analysts and data scientists across Product, Marketing, Finance, and Ops to understand needs and deliver data models that scale.
  • Contribute to self-service analytics enablement by making models discoverable in tools like Omni, Hex, and Sigma, and building user-friendly dashboards and explores.
  • Champion software engineering best practices in analytics: Git workflows, code review, CI/CD for dbt, and reusable SQL patterns.
  • Document business logic and metric definitions in a central data catalog, ensuring clarity and consistency.

Who you are

  • SQL and data modeling expert, with 4+ years in analytics engineering, BI, or related data roles.
  • Skilled in dbt and modern cloud data warehouses (Snowflake, BigQuery, Databricks).
  • Experienced with semantic layers and BI tools (Omni, Looker, Sigma, Hex) to drive metric consistency.
  • Comfortable with orchestration tools (Airflow, Dagster, Prefect) and Git-based workflows.
  • Detail-oriented with a passion for data quality and reliability.
  • Strong communicator who can translate complex data models into clear, actionable insights for technical and non-technical partners.
  • Collaborative teammate with a bias for action, comfortable in a fast-paced startup environment.

Even better if you have

  • Experience in the sports, fantasy, or gaming industry.
  • Background in real-time or streaming analytics.
  • Contributions to the dbt community or open-source analytics projects.
  • Familiarity with data observability platforms (Monte Carlo, Elementary).


Our target starting base salary range for this position is between $160,000 and $190,000, plus target equity. The starting base salary will depend on a number of factors including the candidate’s skills and experience, among other things.

What we can offer you:

  • Unlimited PTO (we're extremely flexible with the exception of the first few weeks before & into the NFL season)
  • 16 weeks of fully paid parental leave
  • Home office stipend
  • A connected virtual first culture with a highly engaged distributed workforce
  • 5% 401k match, FSA, company paid health, dental, vision plan options for employees and dependents

#LI-REMOTE

We're a remote-first company and value in-person connection. That said, we expect everyone to gather 2-3 times per year for team and company offsites, trainings, and more.

This position may require sports betting licensure based on certain state regulations.

Underdog is an equal opportunity employer and doesn't discriminate on the basis of creed, race, sexual orientation, gender, age, disability status, or any other defining characteristic.

California Applicants: Review our CPRA Privacy Notice here. 

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