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 - Compliance

Nium · Bangalore

Nium is the global infrastructure company powering real-time cross-border payments. Founded to deliver the payments infrastructure of tomorrow, today, we are building a programmable, borderless, and compliant money-movement layer that powers transactions between people, businesses, and intelligent systems — enabling banks, fintechs, payroll providers, travel platforms, marketplaces, and other global enterprises to move money instantly, anywhere in the world. 

Co-headquartered in San Francisco and Singapore, with offices in 14 markets and team members across 20+ countries, we take pride in a culture anchored in Keeping It Simple, Making It Better, and Winning Together. 2025 was the strongest year in our 10-year history, with record revenue, record transaction volumes, and EBITDA profitability — and we are now entering one of the most dynamic chapters in our journey. We believe the best work happens face-to-face, and we operate a hybrid model with three in-office days per week to strengthen collaboration, alignment, and innovation. 

We move over $50B annually across a network that spans 190+ countries, 100 currencies, and 100 real-time corridors. We power fast payouts to accounts, wallets, and cards; enable local collections in 35 markets; and support card issuance in 34 countries — all backed by licenses across 40+ markets. 

With over $300M raised to date, Nium offers ambitious builders the opportunity to shape the future of global money movement — at scale. 

The increasing volume, complexity, and regulatory scrutiny of financial‑crime and compliance risks requires advanced, data‑driven capabilities that traditional analytics and manual processes can no longer support. The Compliance Data Scientist will significantly enhance Nium’s ability to detect emerging risks, optimise controls, meet regulatory expectations, and drive operational efficiency across the compliance function. 

This role fills a critical capability gap and directly supports strategic priorities including automation, risk‑based decisioning, model optimisation, data‑quality improvement, and regulatory assurance. Additionally, this role is specifically designed to support activities related to transitioning compliance systems to advanced, data-driven Artificial Intelligence / Machine Learning solutions e.g. Transaction Monitoring detection models. 

Role Summary: 

  • Responsible for development of AI/ML models to identify risks (such as fraud or credit risk) while ensuring these models are auditable, explainable, and compliant with data privacy laws 

  • Understand the coverage and accuracy of the existing rules for anti-money laundering and financial crimes 

  • Support rules management process to ensure rules are performing to expected thresholds    

  • Support the integrity, accuracy, and usability of data across compliance and financial crime functions.  

  • Develops data dashboards to provide visibility of performance of rules and models  

  • Leverage advanced analytics to understand cause and effect relationships  

  • Understand data quality and labelling, perform advanced analysis to identify high predictive strength variables, and work with technology teams on availability of variables.  

 

The increasing volume, complexity, and regulatory scrutiny of financial‑crime and compliance risks requires advanced, data‑driven capabilities that traditional analytics and manual processes can no longer support. The Compliance Data Scientist will significantly enhance Nium’s ability to detect emerging risks, optimise controls, meet regulatory expectations, and drive operational efficiency across the compliance function. 

This role fills a critical capability gap and directly supports strategic priorities including automation, risk‑based decisioning, model optimisation, data‑quality improvement, and regulatory assurance. Additionally, this role is specifically designed to support activities related to transitioning compliance systems to advanced, data-driven Artificial Intelligence / Machine Learning solutions e.g. Transaction Monitoring detection models. 

Role Summary: 

  • Responsible for development of AI/ML models to identify risks (such as fraud or credit risk) while ensuring these models are auditable, explainable, and compliant with data privacy laws 

  • Understand the coverage and accuracy of the existing rules for anti-money laundering and financial crimes 

  • Support rules management process to ensure rules are performing to expected thresholds    

  • Support the integrity, accuracy, and usability of data across compliance and financial crime functions.  

  • Develops data dashboards to provide visibility of performance of rules and models  

  • Leverage advanced analytics to understand cause and effect relationships  

  • Understand data quality and labelling, perform advanced analysis to identify high predictive strength variables, and work with technology teams on availability of variables.  

 

What we offer at Nium  
 
We Value Performance: Through competitive salaries, performance bonuses, sales commissions, equity for specific roles and recognition programs, we ensure that all our employees are well rewarded and incentivized for their hard work. 

We Care for Our Employees: The wellness of Nium’ers is our #1 priority. We offer medical coverage along with 24/7 employee assistance program, generous vacation programs including our year-end shut down. We also provide a flexible working hybrid working environment (3 days per week in the office). 

We Upskill Ourselves: We are curious, and always want to learn more with a focus on upskilling ourselves. We provide role-specific training, internal workshops, and a learning stipend.

We Celebrate Together: We recognize that work is also about creating great relationships with each other. We celebrate together with company-wide social events, team bonding activities, happy hours, team offsites, and much more!  

We Thrive with Diversity: Nium is truly a global company, with more than 33 nationalities, based in 18+ countries and more than 10 office locations. As an equal opportunity employer, we are committed to providing a safe and welcoming environment for everyone.  

Key Responsibilities

  • Design, deploy, and monitor predictive models and AI algorithms to detect anomalies, fraud, or potential breaches  

  • Conduct deep-dive analyses into risk events, identifying root causes to improve risk strategies and operational workflows 

  • Analyze large datasets to identify patterns, anomalies, and emerging risks. 

  • Performs data validation, cleansing, and reconciliation for regulatory reporting. 

  • Ensure alignment with regulatory requirements by building scalable reporting platforms and documenting data protocols  

  • Partner with legal, product, and operations teams to translate complex technical findings into actionable business insights for senior management 

  • Maintains auditability, traceability, and evidence generation within systems. 

Requirements

  • Degree in Statistics, Mathematics, Data Science, Economics, or related quantitative field 

  • 3 years in data science, advanced analytics, or machine‑learning roles. 

  • Proficiency in various model development techniques  

  • Prior experience in financial services, fintech, payments, or consulting would be strongly preferred 

  • Exposure to financial‑crime systems (e.g., transaction monitoring, sanctions screening, case‑management platforms). 

  • Experience supporting compliance operations, investigations, or model governance. 

  • Experience building and deploying ML models in production environments. 

  • Strong analytical rigor, proactive problem-solving, and capability to communicate technical concepts to non-technical partners 

  • Self-motivated, adept in working individually and as part of a global team 

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