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 Science & Measurement Lead

Primark · Dublin, ie

What You’ll Get 

People are at the heart of what we do here, so it’s essential we provide you with the right environment to perform at your very best. Let’s talk lifestyle:

  • Healthcare, pension, and potential bonus.
  • 27 days of leave, plus bank holidays and if you want, you can buy 5 more.

Because Primark is all about tailoring to you, we offer Tax Saver Tickets, fitness centre, and a subsidised cafeteria.
This role is a hybrid opportunity, offering 1-2 days Working from home.

Data Science & Measurement Lead

Because your new ideas are our way new ways of working.
Evolve, your way.

We are seeking a Data Science & Measurement Lead to manage and grow a team of data scientists responsible for building advanced analytics, predictive models, and measurement solutions across Primark. This is a hands‑on role requiring strong technical depth in Databricks, Apache Spark, and SQL.

What You’ll Do as a Data Science & Measurement Lead

We want you to feel challenged and inspired. Here, you’ll develop your skills across a range of responsibilities:

  • Lead a data science team to deliver machine learning models, experimentation frameworks, and measurement solutions that drive measurable business impact.
  • Design, build, and deploy end-to-end ML pipelines and workflows using Databricks, Spark, Python, SQL, and PySpark.
  • Ensure robust operationalisation of models through scalable, reliable data pipelines and production-ready ML systems.
  • Partner closely with engineering teams to optimise distributed compute workloads and uphold data quality, monitoring, and governance standards.
  • Establish and drive best practices in model reproducibility, experiment tracking, and end-to-end ML lifecycle management.
  • Act as a trusted advisor by sharing deep technical expertise, developing team capability, and managing complex delivery plans.
  • Leverage strong retail domain experience—ideally within apparel or grocery—to translate business needs into effective data-driven solutions.

What You’ll Bring  

Here at Primark, we want everyone to feel valued – so please bring your authentic self to work, of course with some other key experience and abilities for this role in particular:

  • Extensive hands-on experience with Databricks, Apache Spark, advanced SQL, and cloud-based lakehouse architectures (Azure, AWS, or GCP), with a strong foundation in statistical modelling and machine learning techniques.
  • Proven ability to deliver measurable commercial value through retail-focused data science use cases such as demand forecasting, pricing and promotion effectiveness, allocation, stock optimisation, and waste or shrink reduction.
  • Strong experience in experimental design and causal inference (e.g., A/B testing, quasi-experiments), with a clear focus on quantifying incremental value and ensuring insights translate into action.
  • Demonstrated experience taking models from prototype to production, establishing clear success metrics, monitoring, governance, and driving adoption across commercial and operational teams.
  • Ability to shape and prioritise the data science roadmap by balancing business value, data readiness, and delivery risk; applies sound commercial judgement informed by market and industry trends.
  • Proven people leader with experience mentoring and developing high-performing data science teams; communicates complex technical concepts clearly to non-technical stakeholders and acts as a trusted advisor to the business.
     

Does this sound like you? Great, because we can’t wait to see what you’ll bring. You’ll be supported within a team of equally capable people, celebrating who you are and aiding you reach your potential. At Primark, we’re excited about our future - and we’re excited to develop yours.  

 

About Primark 

At Primark, people matter. They’re the beating heart of our business and the reason we’ve grown from our first store in Dublin in 1969 to a £9bn+ turnover business and over 80,000 colleagues and over 440 stores in 17 countries today. Our values run through everything we do. In essence, we're Caring and always strive to put people first. We're also Dynamic, bravely pushing the boundaries to stay ahead. And finally, we succeed Together.     

If you need any reasonable adjustments or have an accessibility request, during your recruitment journey, such as extended time or breaks between online assessments, a sign language interpreter, mobility access, or assistive technology please contact your talent acquisition specialist. 

All offers of employment are subject to background checks, including right to work, reference education and for some roles criminal, and financial checks. If you have any concerns, please reach out to our talent acquisition team to discuss. 

Our fashion isn’t one-size-fits-all and neither is our culture. Primark promotes equal employment opportunity, we strive to create an inclusive workplace where people can be themselves, access opportunities and thrive together.