Animated walkthrough · Right place · Right info · Include vs exclude
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.
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JANE DOE Data Scientist jane.doe@email.com | +91-98765 43210 | linkedin.com/in/janedoe | github.com/janedoe | Bengaluru, India
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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.
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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
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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.
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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.
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EDUCATION B.Tech, Computer Science | XYZ University | 2022-2026 CGPA: 8.7/10 | Relevant Coursework: Machine Learning, Statistics, DBMS
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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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