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Anatomy of a Winning Resume

A line-by-line breakdown of where every part of your resume should go, what to write, and — just as important — what to leave out. Built around a real AI/ML/DS resume that clears ATS scanners.

1 
JANE DOE
Data Scientist
jane.doe@email.com | +91-98765 43210 | linkedin.com/in/janedoe | github.com/janedoe | Bengaluru, India
2 
SUMMARY
Data Scientist with 3+ years building production ML for fintech. Shipped a churn model that lifted retention 12% and cut false negatives 32%. Strong in Python, SQL, and deploying models on AWS.
3 
SKILLS
Languages: Python, SQL, R
ML/DS: scikit-learn, pandas, PyTorch, TensorFlow, XGBoost
MLOps & Cloud: Docker, MLflow, AWS (S3, EC2, SageMaker), Git
Viz: Matplotlib, Seaborn, Power BI, Tableau
4 
EXPERIENCE
ML Engineer | TechCorp | Mar 2023 - Present
- Built a real-time fraud model serving 12M transactions/day; cut p99 latency from 220ms to 78ms.
- Designed a feature store on Feast + Redis, reducing retrieval time 80ms to 6ms.
- Led migration to MLflow, adopted by 4 ML teams.
5 
PROJECTS
Customer Churn Prediction (Python, XGBoost) - github.com/janedoe/churn
- Built an end-to-end churn model on a 50K-customer dataset; achieved 0.89 ROC-AUC.
- Engineered 24 features; cut false negatives 32% vs a logistic baseline.
- Deployed via FastAPI + Docker on AWS EC2.
6 
EDUCATION
B.Tech, Computer Science | XYZ University | 2022-2026
CGPA: 8.7/10 | Relevant Coursework: Machine Learning, Statistics, DBMS
7 
CERTIFICATIONS
Andrew Ng's ML Specialization (Coursera) | AWS Cloud Practitioner

PUBLICATIONS / TALKS
'Scaling Real-Time Inference' - MLOps Community Conf 2024

✅ Always do

  • One page if you have under 5 years of experience; two pages absolute max.
  • Single-column layout — ATS systems mangle tables and multi-column designs.
  • Save as a text-based PDF (not a scanned image), then test it with the ATS Scanner on this site.
  • Standard fonts (Calibri, Arial, Inter) at 10-12pt body size.
  • Tailor the keywords to each job description before you apply.
  • Consistent date format and consistent verb tense throughout.

🚫 Never do

  • Photos, logos, icons, or charts that an ATS can't read.
  • Tables, text boxes, and columns for layout.
  • Personal data: age, marital status, religion, gender, full address.
  • Lying or inflating numbers — you must defend every figure in the interview.
  • Spelling or grammar mistakes — they're an instant credibility hit.
  • Generic objectives, declarations, and 'references on request'.

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