Alex Wang, Back-end Developer in Toronto, ON, Canada
Alex Wang

Back-end Developer in Toronto, ON, Canada

Member since November 9, 2021
Alex is a developer with 4+ years of experience in Python, JavaScript, SQL, and R. She enjoys working in both startup and corporate environments and has worked on all stages of the machine learning project lifecycle (research, data processing, model development, testing, and deployment). Passionate about learning new things, Alex has been building web applications through side projects and is looking for projects that allow her to focus on back-end development and API design.
Alex is now available for hire

Portfolio

Experience

Location

Toronto, ON, Canada

Availability

Part-time

Preferred Environment

Slack, VS Code, GitHub, Postman, MySQL Workbench, MongoDB Atlas

The most amazing...

...project I've worked on is a fraud lead generation tool that helped save the company millions of dollars.

Employment

  • Machine Learning Engineer

    2021 - 2021
    Medchart
    • Built a custom named entity recognition model to detect healthcare facilities and providers in scanned documents.
    • Led a team of five annotators to curate labeled datasets needed for machine learning initiatives and set up automated quality control checks.
    • Identified a prioritized list of machine learning applications to improve product offering by meeting with various business teams to understand their needs and surveying state-of-the-art techniques.
    Technologies: Azure, Python, SQL
  • Senior Data Scientist

    2018 - 2021
    Sun Life Financial Canada
    • Built a text classifier to surface fraud leads from web search data, generating over $2 million in savings.
    • Created a document search tool and underlying data ETL process to help identify keyword mentions for marketing opportunities replacing a manual process.
    • Developed a recommender system to predict which product offerings customers are most likely to respond to based on the characteristics of individuals belonging to the same segment.
    • Prototyped a neural network-based outcome prediction model that accounts for complete patient history, improving accuracy.
    • Performed code and methodology reviews of advanced analytics models.
    • Contributed to knowledge sharing among the team by writing tutorials and creating a best practices guide.
    Technologies: AWS, Python, R, SQL, Elasticsearch
  • Programmer Intern

    2017 - 2018
    Roche
    • Supported the development of internal R packages to facilitate and streamline processes for clinical reporting and exploratory data analysis.
    • Wrote classes to create labels and data filters on graphs and tables, complete with unit tests and documentation.
    • Implemented a structured, easy-to-debug approach to turn static code into dynamic code within Shiny modules while returning the reproducible offline code and writing the accompanying tutorial.
    Technologies: R, RStudio Shiny

Experience

  • Application Tracker App

    A JavaScript-based web app that allows users to authenticate, manage job applications (create, edit, and delete applications), and monitor job search progress metrics.

    The back-end components were written in JavaScript with TypeScript, while the front end was written with React and TypeScript. I used Jest for testing and PostgreSQL for data storage.

  • Articles Archiving Tool

    An Airflow-orchestrated workflow to automatically archive (i.e., details written to a Google Sheet) and summarize liked articles from the Pocket app. This workflow was hosted on AWS using MongoDB for storage.

  • Pyopendatato Python Package

    Pyopendatato is a Python package for accessing resources from the City of Toronto's Open Data Portal that supports searching, metadata retrieval, and file downloads.

    It was written in Python 3, with automated tests using Travis CI and automated code coverage generated using Codecov.

Skills

  • Languages

    Python, R, SQL, JavaScript, TypeScript
  • Other

    Machine Learning, Data Visualization, Experimental Design, A/B Testing, Deep Learning, AWS, GCP, Transformers, Natural Language Processing (NLP), fastText, Computational Inference, Bayesian Statistics, CI/CD Pipelines
  • Frameworks

    Flask, Express.js, RStudio Shiny, Jest
  • Libraries/APIs

    Node.js, PyTorch, TensorFlow, Bing API, PySpark, Google Sheets API, React
  • Tools

    VS Code, GitHub, Git, Postman, Apache Airflow, MySQL Workbench, MongoDB Atlas, Pytest, Travis CI, Codecov
  • Platforms

    Azure, Docker
  • Storage

    MongoDB, PostgreSQL, MySQL, Elasticsearch

Education

  • Master of Mathematics in Statistics
    2016 - 2018
    University of Waterloo - Waterloo, ON, Canada

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