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

Jito · Remote, NY Time Zone

About Jito

Jito is an organization with the broad mandate to promote the adoption of Jito Network products, including JitoSOL, the largest DeFi protocol on Solana, and BAM, a platform for neutral block building on Solana. We are both extremely lean and relentlessly effective, and pride ourselves on having built a flat culture that prioritizes empowering multi-talented self starters to develop and pursue their own strategic vision.

About the Role

We're looking for a Data Scientist who thrives on turning messy, high-volume datasets into clear insight and who doesn't need to be pointed at the next problem. You'll work across our blockchain analytics and data infrastructure efforts - building models, running analyses, and surfacing findings that drive product and business decisions. This role is highly autonomous- you’ll independently chase leads, pursue lines of inquiry, and run with optimization opportunities, quantifying impact along the way. Jito is lean, fast, and executes at an elite level. Everyone is expected to have a material impact on the network. Crypto/blockchain domain knowledge is a plus, but what matters most is your ability to think critically, work fluently with data, operate independently, and pick up new domains fast.

What You'll Do

  • Build dashboards, reports, and visualisations that make complex data accessible to technical and non-technical stakeholders

  • Design and execute quantitative analyses on large-scale blockchain and market datasets

  • Identify and scope new data streams that unlock deeper analysis across Jito's products

  • Develop statistical models and heuristics to detect patterns, anomalies, and trends across Jito's existing and emerging product suite

  • Collaborate with engineers and researchers to define metrics, improve complex systems, and drive product improvement

  • Identify new analytical opportunities and propose research directions independently

What We're Looking For

Must-haves

  • 3–5 years of professional experience in a data science, analytics, or quantitative research role

  • Strong SQL skills (ClickHouse / BigQuery / Snowflake) - you're comfortable writing complex queries across seriously large datasets and understand the tradeoffs between executing at different layers of the data stack

  • Proficient in Python for data analysis (pandas/polars, numpy, scipy, matplotlib/plotly)

  • Solid grounding in statistics and probability - you have the judgment to know when a problem demands rigorous statistical methods and when a simpler heuristic will do

  • Demonstrated ability to take ambiguous questions and turn them into structured analyses with actionable conclusions

  • Exceptional written and verbal communication - you can break down a complex problem space for someone who doesn't live in the data

  • Experience executing product data science on 0→1 products - shaping metrics, surfacing insight, and informing direction for products still finding their feet

Nice-to-haves

  • Experience with blockchain data (Solana, Ethereum, or similar) - transaction-level, on-chain analytics

  • Public Dune dashboards or equivalent on-chain analysis you can point us to

  • Exposure to market microstructure, trading data, or DeFi protocol analytics

  • Background in experiment design (A/B testing, causal inference)

  • Surface and publish data-driven insights and communicate them clearly to broad, non-technical audiences

  • 1500+ chess Elo / Immortal in Dota 2 / Master+ in League / Grandmaster in SC2 / or equivalent proof you optimise things for fun