Check Your Resume Before You Apply

Most employers use software (an ATS) to read and rank resumes. See your score and fix it. Free, no signup to check.

PocketHealth Inc.
Data Engineer
Greater Toronto Area

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How it works

Key Takeaways

  • Automated hiring systems can screen or route resumes before human review; ResumeGeni treats ATS scoring as parser-readiness triage, not a hiring prediction (Harvard Business School & Accenture).
  • The most common ATS-readiness problems are missing keywords, incompatible formatting, incomplete fields, and incorrect file types
  • ResumeGeni scores parseability, structure, contact fields, content completeness, skills, and keyword signals, then explains the evidence behind the score

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 use that data in search, review, and matching workflows. Parsing gaps can make a qualified candidate harder to evaluate.

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 signalsJob-specific terms, skills, certificationsKeyword overlap can affect recruiter search visibility and resume-review workflows
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 extraction means important fields may need manual review

What ResumeGeni Checks Before Keyword Matching

Keyword matching only helps after the resume can be read cleanly. ResumeGeni starts with parser-readiness signals before it evaluates wording, skills, and role fit.

  • Readable text: whether the uploaded file exposes selectable text instead of only a scanned image.
  • Standard resume structure: whether contact, summary, work experience, education, and skills sections are easy to identify.
  • Field extraction: whether names, email addresses, phone numbers, employers, titles, dates, degrees, and skills can be mapped into stable fields.
  • Format risk: whether tables, columns, text boxes, decorative icons, headers, footers, or unusual bullets could interrupt parsing.
  • Evidence quality: whether experience bullets include scope, tools, metrics, and outcomes rather than generic duty lists.
  • Keyword coverage: whether relevant tools, certifications, industry terms, and role-specific phrases appear naturally in the resume.

What Your ATS Score Means

The score is a diagnostic signal, not a hiring guarantee. A high score means ResumeGeni can extract and evaluate the resume with fewer warnings. A low score means the resume likely needs structural fixes before keyword tuning matters.

Score RangeReadBest Next Action
90-100Strong parser readiness with few visible gapsTailor keywords and achievements to the target role
75-89Generally readable, but some sections or evidence may be weakFix warnings, add measurable achievements, and tighten skills
60-74Important content may be missing, vague, or hard to mapRepair structure before rewriting bullets
Below 60Parsing or completeness issues are likely holding the resume backMove to a cleaner format and rebuild core sections first

What To Fix First

Start with problems that prevent a system or recruiter from reading the resume. Save small wording changes for after the structure is clean.

PriorityFixReason
1Use a text-based PDF, DOCX, or plain text resumeImage-only files and corrupted exports cannot be reliably parsed
2Use one column and standard headingsPredictable structure improves section and field detection
3Put contact information in the body, not only the headerSome parsers ignore header and footer regions
4Replace vague duties with quantified achievementsSpecific outcomes help both recruiter review and scoring evidence
5Mirror role language truthfullyRelevant keywords help search and review without keyword stuffing

How To Use the Score Without Overfitting

The best use of an ATS score is triage. Fix problems that make the resume hard to parse or hard to evaluate, then stop when the document is clear. Do not chase a perfect score by adding keywords you cannot defend in an interview or by turning every bullet into a list of tools.

Checker signalGood correctionCorrection to avoid
Low parse confidenceMove to a single-column layout, standard headings, and selectable text.Adding more keywords before the resume can be read cleanly.
Weak evidence bulletsRewrite duties into scope, action, tool, and measurable outcome.Inflating impact numbers or copying sample bullets that do not match your work.
Missing role termsAdd truthful tools, certifications, patient loads, stack details, or workflows from your experience.Keyword stuffing a skills section with technologies you have not used.
Thin company fitCompare the resume with the target role and company application guide before applying.Submitting the same generic version to every employer.

Methodology And Limits

ResumeGeni checks format, extraction, content completeness, and keyword signals from the uploaded resume. It does not certify that every employer ATS will parse the file the same way, and it does not predict whether a recruiter will interview you.

For the scoring rubric, privacy notes, and limitations, read the ATS Resume Checker Methodology. For the broader source map behind ResumeGeni guidance, use the research hub and dated research data dashboard. For application context, use the exact company application guide or role guide that matches the job.

What the Checker Can Diagnose

Treat the ATS resume checker as a document-readiness diagnostic, not a hiring prediction. A useful check should tell you whether the resume text can be extracted, whether the major sections are recognizable, whether contact fields are present, whether bullets contain evidence, and whether role language appears naturally enough for a reviewer to understand the match.

Diagnostic areaWhat ResumeGeni looks forBest correction
Text extractionSelectable text, readable file structure, and parser confidence.Use a text-based PDF, DOCX, or pasted text version before changing wording.
Section recognitionStandard headings for contact, summary, experience, education, skills, projects, and certifications.Rename creative headings to conventional resume sections and keep content in the document body.
Evidence qualityBullets with scope, action, tools, and measurable outcomes rather than generic duties.Rewrite the most recent role first, then work backward through older experience.
Role alignmentTruthful keywords, credentials, systems, technologies, and responsibilities that match the target role.Compare the resume with a role guide and a real posting before adding or removing terms.

Pair the Score With a Role Guide

An ATS score is the starting point. After the resume is readable, compare it with the role you are targeting so your skills, bullets, and keywords match the actual posting without keyword stuffing.

Resume pathUse this guide when the checker flagsBest next page
ClinicalMissing license, certification, patient-load, unit, EHR, or care-outcome evidenceRN resume guide
TechnicalThin stack detail, unclear shipped features, missing testing, deployment, or performance evidenceFull-stack developer resume guide or Android developer resume guide
PortfolioCase studies, client scope, shipped work, project outcomes, or collaboration signals are too vagueProduct designer resume guide or Freelancer resume guide
People operationsHRIS, compliance, hiring, retention, employee-relations, or policy examples are missingHuman resources manager resume guide

Where This Checker Fits in the Application Path

Use the checker as a diagnostic gate between drafting and applying. It is strongest when the next action is specific: fix parsing risks, rewrite vague bullets, add missing role evidence, or compare the resume against a real posting. It is weaker when treated as a hiring predictor or a substitute for role judgment.

Signal from the checkerBest next pageReason
Formatting or parsing warningsATS compatibility methodologyReview the scoring categories and limits before changing the file structure.
Weak or generic experience bulletsResume guides by job titleFind role-specific examples and replace duties with evidence, scope, and outcomes.
Missing tools, systems, or certificationsSkills guides by job titleCheck which skills belong in the resume and which should appear only when truthful.
Company-specific application concernsCompany application guidesCompare employer context, ATS signals, and open-role language before final tailoring.

Sources Used For This Checker

ResumeGeni's checker combines product analysis with public resume-writing, occupational, and structured-data references. These sources inform parser-readiness guidance; they do not certify that any employer or ATS vendor will score a resume the same way.

Frequently Asked Questions

Is ResumeGeni free?
Yes. 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 parsed into structured fields such as contact information, experience, education, and skills. The score reflects how cleanly ResumeGeni can extract those fields plus format, content, and keyword signals.
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.

Preferred ATS Checker Resource Spine

Built by ResumeGeni. Methodology, sources, and limitations are documented above. Last updated .

Data Engineer

PocketHealth Inc. · Greater Toronto Area

What if you could personally impact the future of healthcare? As part of the PocketHealth team, you will enable hospitals and clinics across North America — and more importantly, empower over 2 million patients — to discover a better healthcare experience.

PocketHealth is a patient-centric platform that enables hospitals and clinics across North America to share imaging records digitally with patients, instantly and securely. Through our platform, we enable patients to be active and engaged participants in their own care, and take control of their care journey. In addition to image sharing, which is the heart of the PocketHealth platform, we’ve grown our core functionality to enable sharing between hospitals and physicians, as well as instant image retrieval and automated importing capability. PocketHealth is a unified image management solution for over 800 hospitals and clinics across North America. We believe that by placing patients at the center of the record release process, data moves more ethically, easily and securely throughout the care journey, and we’re looking for passionate individuals to help make this vision a reality for millions more patients across North America.

As a Data Engineer, you will help build and maintain the data infrastructure that powers our data-driven solutions, ultimately enhancing the healthcare experience for millions of patients and healthcare providers. You’ll work closely with our Senior Data Engineer and cross-functional partners, with direct mentorship and opportunities to develop your skills across the full data engineering lifecycle. If you're excited about the intersection of data engineering and machine learning, this role offers a clear path to grow in that direction. Ideal candidates will possess a high degree of user empathy and a focus on the quality and speed of our product. Our patients simply can’t afford to wait!

This job posting is for an existing vacancy. The salary range for this position is $100,000 – $130,000 annually, depending on the experience and expertise you bring to the team. Salary is just one part of the story, though; this role is also eligible for equity in the form of stock options and includes a comprehensive health and benefits package. We view our compensation as a total investment in your well-being, designed to support you both in your work and in your life outside of it.

As a Data Engineer, you will help build and maintain the data infrastructure that powers our data-driven solutions, ultimately enhancing the healthcare experience for millions of patients and healthcare providers. You’ll work closely with our Senior Data Engineer and cross-functional partners, with direct mentorship and opportunities to develop your skills across the full data engineering lifecycle. If you're excited about the intersection of data engineering and machine learning, this role offers a clear path to grow in that direction. Ideal candidates will possess a high degree of user empathy and a focus on the quality and speed of our product. Our patients simply can’t afford to wait!

This job posting is for an existing vacancy. The salary range for this position is $100,000 – $130,000 annually, depending on the experience and expertise you bring to the team. Salary is just one part of the story, though; this role is also eligible for equity in the form of stock options and includes a comprehensive health and benefits package. We view our compensation as a total investment in your well-being, designed to support you both in your work and in your life outside of it.

You can do amazing things at PocketHealth. You can positively impact the healthcare journey for millions of people, while building your career and developing your skills. It doesn’t have to be one or the other. It has been a part of our mission since our founding to empower patients & make healthcare accessible to all, and we know this can only be achieved with a team of diverse perspectives that is representative of the Patient & Provider communities we serve. 

People love working here for these reasons and more: working remotely, our competitive salaries and benefits (including stock options for every employee!), four weeks of paid time off, unlimited paid wellness days, extended mental health coverage, and 16 weeks of parental leave top-up.

We’re proud to foster a culture that embraces diversity, equity, and inclusion, and we believe in caring for our employees with the same thoughtfulness we offer our Patients & Providers.

If there are ways we can support you through the recruitment process with an accommodation, please let us know by reaching out to [email protected]. Applications are accepted via posting only.

In this role you will:

  • Build and maintain data models and transformation workflows that support analytics, reporting, and product use cases.
  • Support the development and improvement of data pipelines and systems to process and analyze healthcare data, gaining experience across the full data engineering lifecycle from ingestion and transformation to storage and consumption.
  • Work with Python and SQL to transform, validate, and troubleshoot data across our platform.
  • Contribute to our Databricks-based analytics platform and help improve the usability, quality, and documentation of our datasets.
  • Collaborate with cross-functional teams to understand their data needs and contribute to our data infrastructure roadmap.
  • Gain hands-on exposure to machine learning workflows - from data preparation and feature engineering to model training - with room to grow deeper as the team and your skills evolve.
  • What you’ll need to be successful:

  • 1–2 years of engineering experience in data engineering, analytics engineering, software engineering, or a related field, including strong internship or co-op experience.
  • Bachelor’s degree in Software Engineering, Computer Science, or a related field, or equivalent practical experience.
  • Strong fundamentals in Python and SQL.
  • Hands-on experience working with structured data in an internship, research, academic, or early-career industry setting.
  • Strong problem-solving skills and attention to detail, with a focus on delivering high-quality solutions.
  • A collaborative mindset, strong communication skills, and eagerness to learn in a fast-paced environment.
  • Nice to have:

  • Exposure to Databricks or similar modern data platforms.
  • Practical exposure to machine learning concepts such as model training, feature engineering, or evaluation.