Hammad Farooq hammadfarooq-ai

2x
_{Kaggle Grandmaster}

#15
_{Global Rank}

620+
_Notebooks

154+
_Datasets

5+ yrs
_Experience

About Me

class HammadFarooq:
    def __init__(self):
        self.role       = "Data Scientist & AI Developer"
        self.experience = "5+ years"
        self.focus      = ["Predictive Analytics",
                           "Machine Learning",
                           "LLM / RAG Systems"]
        self.domains    = ["Finance", "Real Estate",
                           "Legal-Tech", "Healthcare", "BI"]
        self.rank       = "2x Kaggle Grandmaster (#15 Global)"

    def what_i_do(self):
        return ("EDA -> Feature Engineering -> Modeling -> "
                "Validation -> Deployment -> Monitoring")

Data Scientist with 5+ years of experience building, deploying, and monitoring machine learning models — classification, regression, clustering, and time-series forecasting — for clients across finance, real estate, legal-tech, healthcare, and enterprise business intelligence.

🔭 Building multi-agent LLM platforms and production ML pipelines
🏆 2x Kaggle Grandmaster — ranked #15 globally in both Datasets and Notebooks
📈 620+ public notebooks · 154+ datasets · fully reproducible experiment repositories
🎓 Invited speaker, AI Technologies Summer School 2026 (Ivan Franko National University, Ukraine)
🎥 Sharing insights on YouTube and Medium
💬 Ask me about ML pipelines, RAG architectures, forecasting, and MLOps on Azure

How I Build ML Systems

flowchart LR
    A([Raw Data]) --> B[EDA &<br/>Cleaning]
    B --> C[Feature<br/>Engineering]
    C --> D{Modeling}
    D --> E[Classification<br/>Regression<br/>Clustering]
    D --> F[Forecasting<br/>ARIMA / TS]
    D --> G[Deep Learning<br/>Transformers / CNN]
    E --> H[Validation &<br/>Evaluation]
    F --> H
    G --> H
    H --> I[FastAPI +<br/>Docker]
    I --> J[Azure ML<br/>Deployment]
    J --> K([Monitoring &<br/>Drift Guardrails])

    classDef src fill:#0F2027,stroke:#38BDF8,stroke-width:2px,color:#ffffff
    classDef step fill:#1f2937,stroke:#38BDF8,stroke-width:1px,color:#e5e7eb
    classDef model fill:#312e81,stroke:#818cf8,stroke-width:1px,color:#ffffff
    classDef ship fill:#064e3b,stroke:#34d399,stroke-width:1px,color:#ffffff

    class A,K src
    class B,C,H step
    class D,E,F,G model
    class I,J ship

Stage	What I Actually Do
🔍 Explore	Statistical EDA, hypothesis & A/B testing, data quality auditing
🧱 Engineer	Feature design, encoding, scaling, leakage checks, PySpark pipelines
🧠 Model	Random Forest, Gradient Boosting, ARIMA, CNN, transfer learning, fine-tuning
📏 Validate	Cross-validation, metric selection, error analysis, calibration
🚀 Ship	FastAPI services, Docker images, CI/CD on GitHub, Azure ML
📡 Monitor	Drift detection, prediction-quality checks, safety guardrails

Tech Stack

🧠 Languages & Data

📊 Analysis & Visualization

🤖 Machine Learning & Deep Learning

🧬 Generative AI & LLM Engineering

⚙️ Backend, Cloud & MLOps

🔗 Automation & Tooling

Where I Spend My Time

pie showData
    title Focus Areas
    "Machine Learning & Modeling" : 35
    "Generative AI / RAG & Agents" : 30
    "Data Engineering & Pipelines" : 20
    "MLOps & Deployment" : 15

A RAG System I Ship

flowchart TB
    subgraph ING[" 📥  Ingestion "]
        D1[Documents] --> CH[Chunking]
        CH --> EM[Embeddings]
        EM --> VS[(FAISS / Chroma)]
    end

    subgraph RET[" 🔎  Retrieval "]
        Q([User Query]) --> HY[Hybrid Search<br/>semantic + keyword]
        VS --> HY
        HY --> RR[Re-rank &<br/>Citation Gate]
    end

    subgraph GEN[" 🧠  Generation "]
        RR --> LLM[GPT-4o / Ollama]
        LLM --> GR{Guardrails &<br/>Entailment Check}
        GR -->|supported| ANS([Cited Answer])
        GR -->|unsupported| ABS([Honest Abstention])
    end

    ANS --> EV[Eval & Logging]
    ABS --> EV

    classDef box fill:#1f2937,stroke:#38BDF8,color:#e5e7eb
    classDef store fill:#312e81,stroke:#818cf8,color:#ffffff
    classDef out fill:#064e3b,stroke:#34d399,color:#ffffff
    class D1,CH,EM,HY,RR,LLM,EV box
    class VS store
    class ANS,ABS,Q,GR out

GitHub Analytics

Achievements & Recognition

🏅	Achievement
🥇	2x Kaggle Grandmaster — Datasets #15 and Notebooks #15 globally
📚	620+ public notebooks and 154+ datasets, thousands of views across the community
🧠	32nd / 2,673 teams — Akkadian Translation competition (fine-tuned ByT5)
🎤	Invited speaker, AI Technologies Summer School 2026 — Ivan Franko National University, Ukraine 70 speakers · 21 countries · 1,335 participants · Certificate of Gratitude
🚀	LabLab.ai Hackathon competitor — shipped working ML solutions under real-world constraints
🧪	Global research challenges — ARC-AGI, Legal Information Retrieval, NVIDIA reasoning benchmarks

Certifications & Education

BS in Data Science
_{Virtual University of Pakistan}

ICS — Computer Science
_{Punjab Group of Colleges}

Let's Build Something

Open to data science, machine learning and AI engineering roles — remote or relocation.

"Data is the raw material — the value is in the decision it enables."

⭐️ From @hammadfarooq-ai — thanks for stopping by!

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