Kunal Kumar itskunalkumar

👨‍💻 About Me

"I replace 'I think' with 'the data shows.'"

I'm a Data Analyst and Data Science & Machine Learning practitioner with a Mechanical Engineering background. I work with SQL, Power BI, Python (Pandas, NumPy, Scikit-learn) and Advanced Excel, and I build end-to-end ML/DL projects that are deployed and live, using TensorFlow/Keras, NLP, Flask, FastAPI, Docker, AWS ECS and CI/CD.

class Kunal:
    role      = ["Data Analyst", "Data Scientist", "ML Engineer"]
    education = "B.Tech Mechanical Engineering, Bihar Engineering University"
    focus     = ["Fraud Detection", "NLP", "Computer Vision", "MLOps"]
    achieved  = "Smart India Hackathon 2023 Finalist 🏆"

    def goal(self):
        return "Turn data into decisions that matter."

📈 Impact at a Glance

🔍 5% → 51%	💳 100,000+	🧠 6+	🌐 5
fraud recall improvement	transactions scored	fraud models evaluated	ML apps deployed live

🎯 90.5%	⚡ ~1 sec	📚 100,000	🗂️ 113
leaf-disease validation accuracy	prediction time on CPU	sentence pairs for translation	skills in the ResuMatch taxonomy

💼 Experience

🏢 Data Science & Analyst Intern

Amdox Technologies · Nov 2025 – Feb 2026

Designed and evaluated 6+ fraud detection models: Logistic Regression, XGBoost, Isolation Forest, One-Class SVM, Autoencoder, graph-based
Raised fraud recall from 5% to 51% by tuning XGBoost with RandomizedSearchCV
Built a serialized real-time scoring pipeline and logged 100,000+ scored transactions for monitoring

🏢 Intern, Language Translation using Neural Networks

Infosys Springboard · Feb 2025 – Apr 2025

Built an English-to-Hindi NMT system with a custom Encoder–Decoder Transformer in TensorFlow/Keras
Trained on 100,000 sentence pairs (IITB corpus) with a 16,000-token SentencePiece BPE vocabulary
Implemented the full pipeline: preprocessing, tokenization, training and autoregressive decoding

🚀 Featured Projects

Hover over a card, then click it to open the project.

Explainable resume matching with Sentence-BERT, a 113-skill taxonomy and a FastAPI service.

Fine-tuned InceptionV3 that detects crop leaf diseases and suggests treatment in about a second.

Modular ML pipeline deployed on AWS ECS Fargate with automated CI/CD.

ML security system for grid-connected microgrids: two-signal detection (XGBoost + Isolation Forest), SHAP explanations and a fail-safe risk policy. A research prototype on a single dataset.

Deep-learning quality control that classifies casting parts as OK or defective with MobileNetV2, Grad-CAM heatmaps, a REST API and a monitoring dashboard.

🧩 How ResuMatch scores a resume (click to expand)

flowchart LR
    A[📄 Resume<br/>PDF / DOCX / TXT] --> C{{🧠 Match Engine}}
    B[💼 Job Description] --> C
    C --> D[Semantic similarity<br/><b>45%</b>]
    C --> E[Required skills<br/><b>30%</b>]
    C --> F[Section alignment<br/><b>15%</b>]
    C --> G[Requirement coverage<br/><b>10%</b>]
    D & E & F & G --> H[🎯 ATS Match Score<br/>+ skill-gap explanation]

☁️ How the Student Performance Predictor is deployed (click to expand)

flowchart LR
    A[👨‍💻 git push] --> B[⚙️ GitHub Actions<br/>5-step CI/CD]
    B --> C[🐳 Docker build]
    C --> D[📦 Amazon ECR]
    D --> E[🚀 ECS Fargate<br/>Gunicorn + Flask]
    E --> F[🌐 Application<br/>Load Balancer]
    F --> G[🙋 User]

🛠️ Tech Stack

📊 Data Analytics & BI

🐍 Programming & Data Science

🤖 Machine Learning & Deep Learning

🚢 Deployment & Tools

🗄️ Databases

📊 GitHub Analytics

🧊 My Contributions in 3D

🏆 Achievements & Certifications


🥇 Finalist, Smart India Hackathon 2023 (PS Code: SIH1302)	View Credentials
☁️ Google Cloud: Data Analytics Certificate	View Credentials
🌐 Cisco Networking Academy: Data Analytics Essentials	View Credentials

🎯 Currently

🔭 Going deeper into fraud analytics, NLP and MLOps
🌱 Learning to make ML systems explainable and production-ready
💼 Open to Data Analyst / Data Scientist / ML Engineer roles
💬 Ask me about Power BI, fraud detection, deploying ML on AWS

🤝 Let's Connect

⭐ If you like my work, drop a star on a repo, it means a lot!

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