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es65/README.md

Data scientist with a strong background in biotechnology and entrepreneurship. Formal training in applied and genomic data science (MIT, Johns Hopkins) with 4+ years of experience. Skilled in Python, machine learning, and data visualization, with experience in SQL and AWS cloud tools. Eager to leverage expertise in data science to drive impactful business insights and innovative user experiences in a data science or ML-focused role.

Currently building an iOS app that provides advanced metrics and AI-coaching for serious mountain bike riders.

Core Technical Skills

  • Languages & Tools: Python, SQL (PostgreSQL, SQLite), Bioconductor (R), Bash, C++ (basic)
  • Libraries & Frameworks: Pandas, NumPy, Scikit-learn, TensorFlow, Matplotlib, Plotly/ Dash, Seaborn
  • Cloud & DevOps: AWS (EC2, RDS, S3), GitHub, Docker
  • Data Science & ML: Supervised learning (classification, regression), deep learning (neural networks), unsupervised learning (PCA, t-SNE, HMM, clustering), time series analysis, feature engineering, cross-validation, hyperparameter tuning, ETL / data pipeline automation
  • Other: Experimental design, statistical modeling, process automation, scientific communication

Pinned Loading

  1. MtbViz MtbViz Public

    Cool metrics and a visualization tool for serious mountain bike riders. Works with a smartphone and the Sensor Logger app to collect GPS, accelerometer, and gyroscope data.

    Python

  2. ADSP ADSP Public

    MIT Applied Data Science Program Capstone: Facial Emotion Recognition with Neural Nets

    HTML

  3. fitness-tracker fitness-tracker Public

    Machine Learning Fitness Tracker App, based on Dave Ebbelaar: https://www.youtube.com/playlist?list=PL-Y17yukoyy0sT2hoSQxn1TdV0J7-MX4K

    Python

  4. ISLP ISLP Public

    Labs and other work from Introduction to Statistical Learning with Python

    Jupyter Notebook