Analyze. Model. Impact.
Data Scientist Portfolio Examples
See how data scientists and ML engineers present their work, papers, and projects. Learn how to make your data portfolio stand out — then build your own with Folify.
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Dr. Priya Patel
ML Engineer · NLP Researcher
Model Accuracy by Dataset
SentimentBERT94.2% F1
TabularBoost↑ 31% lift
What to include in your data scientist portfolio
These are the sections that make data scientist portfolios stand out.
ML / Data Projects
End-to-end projects with data, method, and results
Technical Skills
Python, SQL, ML frameworks, cloud platforms
Publications & Research
Papers, blog posts, or Kaggle notebooks
GitHub Activity
Demonstrates consistent coding and open source work
Work Experience
Companies, roles, and measurable impact
Recommended blocks
Add these Folify blocks to build a complete data scientist portfolio.
HeaderSkillsProjectsGitHub StreakExperienceEducation
3 tips for data scientist portfolios
01
Always include metrics — accuracy, lift, time saved
02
Link to Kaggle, notebooks, or published papers
03
Show GitHub contributions to prove coding chops
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