# Data Scientist Resume

Templates designed for analytics and ML roles at top Indian companies. Include the right keywords to pass ATS screening.

## Key Points
- Infographic-style resumes with charts showing your 'Python proficiency at 90%' get parsed as garbage by ATS systems.
- Recruiters at analytics firms spend 6 seconds on a resume — fancy visuals slow them down, not impress them.
- Data visualization skills should be proven by your projects, not by how colorful your resume looks.
- Photos, logos, and graphic headers are stripped by ATS — your name may literally disappear.

## What to Include
- Technical skills: Python, R, SQL, TensorFlow, PyTorch, Spark, Tableau, Power BI
- ML model metrics: accuracy, F1 score, AUC-ROC with business impact
- Research papers or Kaggle competition rankings if applicable
- Business impact of your models: revenue generated, cost saved, efficiency improved
- Domain expertise: fintech, healthcare, e-commerce, etc.

## Common Mistakes
- Listing tools without showing what you built with them
- Not quantifying model performance or business impact
- Using jargon without context — explain impact in business terms
- Putting Kaggle rank but no real-world project experience
- Fancy resume layouts that break when parsed by ATS

## Keywords to Use
- Machine Learning
- Deep Learning
- Natural Language Processing
- Computer Vision
- Statistical Modeling
- A/B Testing
- Feature Engineering
- Data Pipeline
- Python
- TensorFlow
- PyTorch
- SQL
- Spark
- Tableau
- ETL

## Sample Bullet Points
- Built a customer churn prediction model using XGBoost achieving 92% AUC-ROC, reducing churn by 18% and saving $2.3M annually
- Designed and deployed an NLP-based sentiment analysis pipeline processing 500K+ customer reviews daily with 87% accuracy
- Created an automated feature engineering framework reducing model development time by 60% across 5 data science teams
- Led A/B testing framework implementation that increased conversion rates by 23% through data-driven product decisions

## Recommended Templates
- [professional](https://stepupcareer.in/builder?template=professional)
- [crisp](https://stepupcareer.in/builder?template=crisp)
- [compact](https://stepupcareer.in/builder?template=compact)

## Frequently Asked Questions

**What skills should a data scientist resume highlight?**
Focus on Python/R, SQL, ML frameworks (TensorFlow/PyTorch), statistics, and business impact. List tools you've actually used in production, not just coursework.

**Should I include Kaggle competitions on my resume?**
Yes, if you have notable rankings (top 10%). But always pair them with real-world projects that show business impact.

**How do I show ML model results on a resume?**
Use metrics with business context: 'Built fraud detection model (95% precision, 88% recall) preventing $1.2M in annual losses' — not just technical metrics alone.

**Is a data science portfolio necessary?**
Highly recommended. Link to your GitHub with clean, documented projects. Recruiters at Indian analytics firms actively check portfolios.

**What resume format works for data science roles?**
Single-column, ATS-friendly format. Lead with a skills section, then experience with quantified achievements. Keep it to 1-2 pages.

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