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hienphan161/README.md

Hey there! I'm Hien Phan.

Data Analyst | Machine Learning Engineer | MLOps Enthusiast

I'm a data professional with over 4 years of experience in roles including Data Analyst and Machine Learning Engineer. My passion lies in designing, building, and deploying scalable, end-to-end machine learning systems that solve real-world business problems.

  • 🔭 I specialize in MLOps, Generative AI, and building robust Data Engineering pipelines.
  • ☁️ My core expertise is within the Google Cloud Platform (GCP) ecosystem.
  • 🌱 I'm a detail-oriented problem solver, driven by the challenge of turning complex data into impactful, automated solutions.

🚀 What I'm Currently Exploring

I believe in continuous learning and am always seeking opportunities to expand my skill set. Right now, I'm particularly focused on:

  • Large-Scale Data Processing with PySpark.
  • Modern Data Transformation workflows using dbt.
  • Handling Unstructured Data with NoSQL databases like MongoDB.
  • Expanding my knowledge of multi-cloud data architectures.

🛠️ My Core Technical Toolkit

This is a snapshot of the technologies I use regularly and have hands-on experience with.

CategoryTechnologies
Programming LanguagesPython, SQL, Kotlin, TypeScript, Bash Scripting
Data Science & MLPandas, PyTorch, Hugging Face
MLOpsModel Training & Evaluation, Testing (Pytest), API Serving (REST, gRPC)
Generative AILangChain, LangSmith, Prompt Engineering, LLMs
Data EngineeringAirflow, Kafka, Google Cloud Pub/Sub, Dimensional Modeling
Infrastructure & CI/CDTerraform, Kubernetes, Docker, GitLab, Jenkins, Git
DatabasesBigQuery, PostgreSQL, MySQL
ObservabilityPrometheus, Grafana, Elasticsearch

📫 Reach me on

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  1. diabetes-predictiondiabetes-predictionPublic

    Production-grade MLOps project demonstrating end-to-end machine learning operations: from model training to deployment with CI/CD, monitoring, and Kubernetes orchestration.

    Python

  2. titanic-challenge-pipelinetitanic-challenge-pipelinePublic

    A machine learning project predicting Titanic passenger survival through domain-driven feature engineering and Random Forest classification.

    Python

  3. chicago-fare-predictionchicago-fare-predictionPublic

    An end-to-end machine learning pipeline for predicting taxi fares in Chicago using real-world data from the City of Chicago's open data portal.

    HTML

  4. skynet-transportation-instituteskynet-transportation-institutePublic

    A comprehensive ML pipeline for Boston rideshare transportation analysis, forecasting, and multi-objective optimization.

    Python

  5. documents-analysis-with-ragdocuments-analysis-with-ragPublic

    AI-Powered Document Analysis — Generate, analyze, and query customer service tickets using advanced LLM techniques including RAG, structured extraction, and adaptive reranking.

    Python

  6. translation-multi-agent-collaborationtranslation-multi-agent-collaborationPublic

    A simple translation system using multi-agent collaboration. Three AI agents work together to produce high-quality translations: Translator Agent, Editor Agent and Technical Reviewer Agent.

    Python