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paul-london/README.md

Paul London

Data Scientist | Python, SQL, Machine Learning | Bioinformatics | Molecular Diagnostics

I’m a Molecular Technologist turned Data Scientist with a strong foundation in molecular biology, bioinformatics, and applied machine learning.
With experience working in both lab and data environments, I build data‑driven solutions that blend scientific insight and engineering discipline.

I’m passionate about:

  • Building reproducible ML pipelines and workflows
  • Translating biological data into actionable insights
  • Bridging wet‑lab science with computational biology and data engineering

🎯 Career Goals

I am focused on applying data science, AI/ML, and bioinformatics to translational research, clinical genomics, and biotech analytics. Open to opportunities in biotech, pharma, healthcare, and other data-driven roles.

🛠️ Skillset

Area Skills
📊 Data Science & ML Python, SQL, pandas, scikit-learn, regression, classification, clustering, ML pipelines, applied AI, hyperparameter tuning, Optuna, model monitoring
☁️ Cloud, Deployment & MLOps Docker, Streamlit, GCP, Render, pipeline automation, reproducible environments, model deployment, pipeline orchestration
📈 Data Visualization & Analysis Matplotlib, Seaborn, Plotly, Tableau, Power BI, literature review, trend analysis, statistical modeling, hypothesis testing
🧬 Bioinformatics & NGS Genomics analysis, RNA therapeutics, variant calling, BLAST/Entrez, protein modeling
🔬 Lab Automation & Support Robotics, lab instrumentation troubleshooting, LIS integration
🧾 Regulatory & Quality CAP/COLA/CLIA standards, SOP management
🚀 Collaboration & Communication Training, technical presentations, troubleshooting guidance, communicating with non-technical stakeholders

💻 Tech Stack

Languages Data / ML Deep Learning / AI Visualization Cloud / Deployment Dev Tools Bioinformatics
Python Pandas OpenAI Matplotlib Streamlit Git Biopython
SQL NumPy PyTorch Seaborn GCP GitHub BLAST
Bash SciPy TensorFlow Plotly Docker VSCode Entrez
Scikit-Learn HuggingFace Tableau Render Jupyter

🔭 Projects

  • Biotech Trend Intelligence

    • An intelligence platform showcasing automated trend extraction from RSS feeds across the biotech ecosystem.
    • Interactive dashboard allowing exploration of recent trends.
    • Submitted as a Concierge Agent for Google AI Agents Intensive Capstone Project.
  • Machine Learning Classification of Structural Protein Sequences for Drug Discovery

    • Comparison of different Machine Learning approaches (NLP, LSTM, LLM) to predict protein functional class from sequence alone.
  • Property Type Prediction Dashboard

    • Machine learning project completed during an externship with Berkshire Hathaway HomeServices.
    • Data-driven dashboard to classify real estate listings by property type (detached, attached, or condo) using MLS data.

    Note: The dataset contains synthetic data to replace proprietary information while preserving structure and patterns for demonstration purposes.

  • Park Hopper Routes

    • Route optimization algorithm for a summer vacation roadtrip created in collaboration with Software Engineers.
    • Interactive website to plan a route for a summer roadtrip through national parks and provide helpful travel tips.
  • Bioinformatics

    • Bioinformatics exercises and exploratory projects from academic study and personal exploration, as well as NGS analysis pipelines.
    • Coursework
    • NGS Analysis Pipelines
  • TripleTen Data Science Projects

    • Machine learning and data analysis projects from the TripleTen Data Science Professional Training Program.

📫 Contact

Feel free to reach out, I am always looking for opportunities and networking!

Pinned Loading

  1. Bioinformatics Bioinformatics Public

    Bioinformatics coursework and NGS Analysis projects.

    Jupyter Notebook 1

  2. TripleTen-Data-Science-Projects TripleTen-Data-Science-Projects Public

    TripleTen Data Science Professional Training Program projects.

    Jupyter Notebook 1