Equipped with experience in Machine Learning and Data Visualization, I began in web development, working in full-stack MEAN(MongoDB, Express, AngularJS, Node.js), and into React.js. I discovered a passion for data, analytics, and visualizations when I began working with D3.js. Since then, I have learned and applied Machine Learning algorithms and theory into my side projects and work.
San Francisco, California
As a leader in the field of Artificial Intelligence, IBM Watson Health is the transference of AI into revolutionizing the Healthcare industry. As a developer on the Watson Health team, I prospect new features and manage the API usages of the premier commercialized AI product. Watson Health has become a standard for commercialized AIs and all decisions made will have an ongoing impact in the feature ventures of IBM Watson.
Beginning as an internship, and continuing as a full-time contractor during school and for a period after graduation, I was primary developer in reconstructing the checkout cart and summary page of a leader in the CPQ field. Constructed in AngularJS for enterprise use, I optimized existing features and introducing innovative new features on our cart page. Efficiency and agile development were necessary when part of the core product team and responsible for satisfying the demands of over 300 client companies with client contracts worth upwards of $12m.
Educating and debugging a department of 400 Computer Science students across the entire curriculum of 11 classes, I gained essential skills such as understanding existing code, confidence in communicating how code works with others, and interpersonal skills necessary to work with other developers.
D3.js, Python, Data Visualization, Matplotlib, Machine Learning, Artificial Intelligence, Natural Language Processing
Whiteboarding, Prototyping, Presentations, Interpersonal Communication, Agile Development
Using tools such as D3.js, IBM Watson's Personality Profiler, and Python libraries such as NLTK, beautifulsoup and sklearn, I used natural language processing and machine learning to construct web visualizations all 10 seasons of Friends. After web scraping the corpus of 1.25m words, I observed relationships between people, N-grams of main characters and personality profiles of each character.
I analyzed and visualized a collection of 2000 Chipotle orders and 50 menu items to construct 3 visualizations in D3.js, made to deduce and observe trends, outliers and statistical value of the data set. The focus of this project was to create effective data visualizations on a modern platform with cognizance of UI and UX internations.
I created a full-stack web application built on Node.js, React.js, MongoDB and Express to build an independent web application. By creating an online database with a functional API, deploying a full stack applications onto the web, I created a system where users could submit, rate, and manage content based on learning styles.