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Data Science & AI

Data Scientist & AI Engineer README Template

This template helps ML engineers and data scientists present research, experimentation, and applied AI work in a way that feels technical and trustworthy.

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Designed for

  • Machine learning engineers building practical products.
  • Researchers sharing publications, models, and experiments.
  • Analysts and engineers who want a crisp technical profile.

Included in the layout

  • Python, PyTorch, SQL, and Jupyter-friendly sections.
  • Visible metrics and project snapshots.
  • Structured storytelling around impact and learning.

Live Preview & Raw Markdown

JK
🧠 Dr. Jordan Kim — AI Research Engineer
ML Research Engineer · NLP · LLMs · Kaggle Grandmaster 🏆
Kaggle Grandmaster Google Scholar HuggingFace

🔬 Research Profile

researcher = {
  "name": "Dr. Jordan Kim",
  "kaggle_rank": "Grandmaster (#47 globally 🏆)",
  "papers_published": 14,
  "citations": 3_847,
  "h_index": 18,
}
14
Papers
3.8k
Citations
18
h-index
#47
Kaggle Rank

🛠️ Technical Toolkit

ML & Deep Learning

PyTorch TensorFlow HuggingFace CUDA Python Jupyter

Data Engineering

Apache Spark Apache Airflow SQL Pandas dbt

📚 Selected Publications


🏆 Kaggle Competition Results

CompetitionResultMedal
Google – Sign Language Recognition1st / 2,742🏅 Gold
LLM Science Exam1st / 2,147🏅 Gold
BirdCLEF 20232nd / 1,856🥈 Silver
Feedback Prize – ELL4th / 2,654🥉 Bronze
<!-- ======================================================== 🤖 GitHub Profile README — Data Scientist & AI Engineer Replace all placeholders with your own information! ======================================================== --> # 🧠 Dr. Jordan Kim — AI Research Engineer <p align="center"> <img src="https://readme-typing-svg.demolab.com?font=JetBrains+Mono&weight=700&size=20&pause=1000&color=7C3AED&center=true&vCenter=true&width=600&lines=ML+Research+Engineer;Deep+Learning+Practitioner;NLP+%7C+Computer+Vision+%7C+LLMs;Kaggle+Grandmaster+🏆;Published+AI+Researcher" alt="Typing SVG" /> </p> <p align="center"> <img src="https://img.shields.io/badge/Kaggle-Grandmaster-20BEFF?style=for-the-badge&logo=kaggle&logoColor=white" /> <img src="https://img.shields.io/badge/Google_Scholar-4285F4?style=for-the-badge&logo=google-scholar&logoColor=white" /> <img src="https://img.shields.io/badge/HuggingFace-FFD21E?style=for-the-badge&logo=huggingface&logoColor=black" /> <img src="https://komarev.com/ghpvc/?username=your-username&color=7C3AED&style=for-the-badge&label=PROFILE+VIEWS" /> </p> --- ## 🔬 Research Interests ```python researcher = { "name": "Dr. Jordan Kim", "affiliation": "AI Research Lab @ [University/Company]", "phd": "Computer Science — NLP Specialization (2021)", "focus_areas": [ "Large Language Models (LLMs) & RLHF", "Multimodal Learning (Vision + Language)", "Efficient Deep Learning (Quantization, Pruning)", "Graph Neural Networks for Drug Discovery", "Causal Inference in ML Systems", ], "kaggle_rank": "Grandmaster (#47 globally 🏆)", "papers_published": 14, "citations": 3_847, "h_index": 18, "open_datasets_released": 6, } ``` --- ## 🛠️ Technical Toolkit ### Machine Learning & Deep Learning ![PyTorch](https://img.shields.io/badge/PyTorch-EE4C2C?style=for-the-badge&logo=pytorch&logoColor=white) ![TensorFlow](https://img.shields.io/badge/TensorFlow-FF6F00?style=for-the-badge&logo=tensorflow&logoColor=white) ![HuggingFace](https://img.shields.io/badge/HuggingFace-FFD21E?style=for-the-badge&logo=huggingface&logoColor=black) ![scikit-learn](https://img.shields.io/badge/scikit--learn-F7931E?style=for-the-badge&logo=scikit-learn&logoColor=white) ![JAX](https://img.shields.io/badge/JAX-9D38BD?style=for-the-badge&logo=google&logoColor=white) ![CUDA](https://img.shields.io/badge/CUDA-76B900?style=for-the-badge&logo=nvidia&logoColor=white) ### Data Engineering & Analytics ![Python](https://img.shields.io/badge/Python-3776AB?style=for-the-badge&logo=python&logoColor=white) ![Apache Spark](https://img.shields.io/badge/Apache_Spark-E25A1C?style=for-the-badge&logo=apachespark&logoColor=white) ![Apache Airflow](https://img.shields.io/badge/Apache_Airflow-017CEE?style=for-the-badge&logo=apache-airflow&logoColor=white) ![SQL](https://img.shields.io/badge/SQL-003B57?style=for-the-badge&logo=sqlite&logoColor=white) ![dbt](https://img.shields.io/badge/dbt-FF694B?style=for-the-badge&logo=dbt&logoColor=white) ![Pandas](https://img.shields.io/badge/Pandas-150458?style=for-the-badge&logo=pandas&logoColor=white) ### Experimentation & MLOps ![MLflow](https://img.shields.io/badge/MLflow-0194E2?style=for-the-badge&logo=mlflow&logoColor=white) ![Weights & Biases](https://img.shields.io/badge/Weights_&_Biases-FFBE00?style=for-the-badge&logo=weightsandbiases&logoColor=black) ![Jupyter](https://img.shields.io/badge/Jupyter-F37626?style=for-the-badge&logo=jupyter&logoColor=white) ![Docker](https://img.shields.io/badge/Docker-2496ED?style=for-the-badge&logo=docker&logoColor=white) ![AWS SageMaker](https://img.shields.io/badge/AWS_SageMaker-FF9900?style=for-the-badge&logo=amazon-aws&logoColor=white) --- ## 📚 Selected Publications | Year | Title | Venue | Citations | |------|-------|-------|-----------| | 2024 | [ContextBench: Evaluating LLMs on Long-Context Reasoning](https://arxiv.org/abs/2024.xxxxx) | NeurIPS 2024 | 234 | | 2023 | [EfficientMamba: State Space Models at Scale](https://arxiv.org/abs/2023.xxxxx) | ICML 2023 | 891 | | 2023 | [MultiModal-CLIP: Extending CLIP for Tabular Data](https://arxiv.org/abs/2023.xxxxx) | EMNLP 2023 | 412 | | 2022 | [GNN-Drug: Graph Attention Networks for Drug Discovery](https://arxiv.org/abs/2022.xxxxx) | Nature MI | 1,204 | --- ## 🏆 Kaggle Competition Results | Competition | Result | Medal | |-------------|--------|-------| | Google – Isolated Sign Language Recognition | 🥇 1st / 2,742 teams | 🏅 Gold | | LLM Science Exam | 🥇 1st / 2,147 teams | 🏅 Gold | | BirdCLEF 2023 | 🥈 2nd / 1,856 teams | 🥈 Silver | | Feedback Prize – English Language Learning | 🥉 4th / 2,654 teams | 🥉 Bronze | --- ## 📊 GitHub & Research Stats <p align="center"> <img height="180em" src="https://github-readme-stats.vercel.app/api?username=your-username&show_icons=true&theme=tokyonight&hide_border=true&bg_color=0d1117&title_color=7C3AED&icon_color=9D38BD" /> <img height="180em" src="https://github-readme-stats.vercel.app/api/top-langs/?username=your-username&layout=compact&langs_count=7&theme=tokyonight&hide_border=true&bg_color=0d1117&title_color=7C3AED" /> </p> --- ## 🤝 Let's Collaborate Open to: **ML Research Collabs · Speaking Engagements · Kaggle Teams · Consulting** <p align="center"> <a href="https://scholar.google.com/citations?user=your-id"><img src="https://img.shields.io/badge/Google_Scholar-4285F4?style=for-the-badge&logo=google-scholar&logoColor=white" alt="Google Scholar" /></a> <a href="https://huggingface.co/your-username"><img src="https://img.shields.io/badge/HuggingFace-FFD21E?style=for-the-badge&logo=huggingface&logoColor=black" alt="HuggingFace" /></a> <a href="https://kaggle.com/your-username"><img src="https://img.shields.io/badge/Kaggle-20BEFF?style=for-the-badge&logo=kaggle&logoColor=white" alt="Kaggle" /></a> </p> --- <p align="center"><i>🧠 From <a href="https://github.com/your-username">your-username</a> — Advancing AI, one commit at a time.</i></p>

Section-by-Section Architecture Breakdown

Engineering managers and technical recruiters review dozens of GitHub profiles every day. They spend an average of 10 to 15 seconds scanning a candidate's profile README. This template is structured to maximize scanning velocity and convey technical capability instantly:

01. Animated Hero & Title
Uses SVG typewriter text to state your core title and stack immediately without forcing the reader to scroll.
02. Tech Stack Shields
Standardized Shields.io badges enable instant visual categorization of languages, frameworks, and cloud tooling.
03. Featured Project Matrix
Replaces plain repo links with a 3-column table showing project purpose, tech stack, and direct live demo links.

Before vs. After Profile Impact

❌ Default / Unoptimized Profile
Blank repository README, generic bio ("I like building stuff"), missing live demo links, no contact info for recruiters.
✅ ReadmeDesign Optimized Profile
Clear role positioning, standardized tech badges, 3x recruiter response rate, live demo links, and active commit streak cards.

Recruiter & Engineering Lead FAQ

Q: How many pinned repositories should I include?
A: We recommend 2 to 4 high-quality repositories. Each repository should have a live demo link, a clean README file, and explicit technical details explaining your architectural choices.
Q: Do GitHub stats cards update automatically?
A: Yes! Dynamic widgets like github-readme-stats fetch real-time data directly from the GitHub API every time someone views your profile.
Q: How do I test my README before pushing live?
A: You can paste your Markdown into our Live README Sandbox or audit your profile with our README Analyzer Tool before committing.