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Hi, if you’re some kind of recruiter or hiring manager, you’ve come to the right place. This page details my qualifications and portfolio in detail. For a briefer, more clinical overview, please see my résumé.
Basic details
I have been working at MAQ Software since May 2023 doing mostly project management and consulting work. Before that I graduated from University of Washington with a computer science degree. I am leaving on September 30th because of my move to New York.
What I’m looking for
I’m looking for a full-time job in software engineering or data analytics, preferably in an environment where I can can apply statistics or machine learning techniques. A web development job (which I can do full-stack, or as just frontend or backend) would also suit me well. I would accept a job outside of my areas of expertise as well, as long as the work would be fulfilling and training would be available to help me succeed.
I am looking for a job with competitive pay in the NYC area. I would prefer a hybrid work model, but I would also accept fully in-person or remote work if needed.
Work history
Software data operations engineer, MAQ Software. May 2023 to present. Redmond, WA. This is my first full-time job. I lead an offshore team of five developers and another one of three developers. I can’t disclose the specific clients or projects, but we primarily do data engineering and presentation work. The primary technologies I’ve used in this job are Microsoft Fabric / Synapse / Databricks (which are integrated platforms for PySpark and Spark SQL notebooks) and Power BI (a data presentation technology similar to Tableau). This job has given me hands-on experience with the Microsoft Azure and Microsoft Office ecosystems, and it has also taught me a great deal about working with clients and managing projects.
My most notable accomplishment at MAQ is a project I started in November 2023 that delivered critical insights to a leadership team upon its completion in May; we continued development afterwards in preparation for its use next year. While I can’t disclose specifics due to my NDA, here are are some key outcomes of the project:
- We developed pipelines to deliver hundreds of metrics, refreshed daily, based on dozens of source tables.
- The relevant stakeholders earned an internal award in their company upon the project’s completion.
- We reduced the load time of an intricate metric from several minutes (as implemented in the source system we were required to match) to just 3 seconds. I devised the optimization approach and debugged several edge cases for this metric.
In addition to this project and several others like it, I earned the DP-600 Microsoft Fabric certification using the skills I developed at MAQ.
Software engineering intern, Spadafy Inc. June to September 2021. Remote. I made a helpdesk app for IT people to field support tickets from users and send them messages. This also involved making a tool that would let IT people customize what fields were on the support ticket creation form. The centralized helpdesk application was made in Django and React. I also did some work on the client app for submitting the tickets, but this position ended before I finished. The client app was in C#.
Machine learning intern, John Snow Labs. June to September 2020. Remote. I made demo applications of John Snow Labs’ machine learning models, to be displayed on the company’s website. The demos were made with Python and Streamlit. I collected the data the demos were based on, then processed it in Jupyter notebooks using the company’s SparkNLP and SparkOCR models.
Math tutor, Mathnasium. April to July 2017, June to September 2019. Mercer Island, WA. I tutored children of all ages in math. (Mostly elementary and middle school, but ranging from pre-K to high school.) This mostly consisted of grading worksheets and explaining unfamiliar concepts that students were struggling with.
Machine learning engineer, Tupl. July to August 2017. Bellevue, WA. I developed a tool using Python, numpy and pandas to evaluate and present the results of a machine learning algorithm. (This was a short internship.)
Education
I graduated from the University of Washington in December 2022. I got my B.S. in Computer Science (data science track) and my GPA was 3.79. For a brief time I was also a double-major in that and ACMS1, which means I’ve taken more statistics and applied math courses than a typical CS grad.
Before that I went to Mercer Island High School, where I graduated in 2019 with a 3.93 GPA.2
My skills
Programming languages: I have extensive experience with Python, Javascript/Typescript, Java, HTML/CSS, SQL, and R. I have some experience with PHP, C, C#, Rust, MATLAB, and Unix shell scripting.
Web technologies: I have extensive experience with Django, Node, React, Next, Svelte, socket.io, Express, npm, and yarn.
Data science/AI technologies: I have extensive experience with numpy, pandas, ggplot, dplyr, and Jupyter notebooks. I have some experience with PyTorch, Spark, and d3.js.
Other tools: I have extensive experience with git and LaTeX. I have some experience with nginx.
I have certain broader skills, as well. I can scrape, process, and clean data from the internet. I can use statistical and numerical techniques to make inferences from data, and I have practice designing methodologies that use these techniques correctly.3 I can write useful documentation. I can design logical and extensible APIs. I can design websites that are useful, aesthetic, and easy to navigate. And I can write clear prose with correct grammar and punctuation.
Other significant projects
Arcade
I built an arcade site (currently with three games) starting in spring 2022. It is made using Typescript, SvelteKit, socket.io, and Express, and it is hosted on a cloud server using nginx.4 You can find the code here. Because the project is solo and still in progress, the documentation, style, and futureproofing may not be as good as they could be. However, this project is quite large (thousands of lines of code), and I am proud of certain accomplishments within it, including:
- a word game solver for Daily Q-less that allows me to evaluate the difficulty of randomly generated puzzles;
- a viewer made in PIXI that animates fights in Mayhem Manager;
- a script (
set-up-test-rooms.ts
) that vastly simplifies and speeds up the testing of the games, and includes a macro system to save redundant work when making test cases; - and a configuration using Vite to allow websockets to work alongside the hot-reloading dev server.
This site was based on my older game, Siphon State, which is no longer online but can be viewed in its GitHub repository. This game was made using most of the same tools, except instead of using SvelteKit, it used React and Next.
This website
This site (the one you are on) is one of my other major undertakings, made in fall 2021. The code is here. It is made using Django. I customized the markdown extensions and I wrote my own HTML templates.
The previous version of this site (code here) was made in React and Next, hosted as a static site. You can see some screenshots of it here.
There is an even older version of the site made in PHP and handwritten HTML/CSS. It was my first experience with web development and in fact I do not have a repo of it because I did not use version control back then.
TagPro statistical analyses
In 2020 I made a series of over twenty statistical analyses of data from the webgame TagPro. The analysis was done in Python and R (later Rust and R), mostly in the dplyr framework. The data was derived from the website tagpro.eu. While I would not like to link my professional profile directly to a gaming account, I will link some of the data visualizations I created: 1 2 3 4 5 6 7 8 9 10
These were each accompanied with an explanation of the methodology behind them, and a thorough analysis of the results, taking care to accurately present the conclusions and their level of uncertainty.
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Applied Computational and Mathematical Studies. Basically computer science + statistics + applied math. ↩
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I also got a 1520 on my SAT and a 35 on my ACT, and I was a National Merit Scholar. ↩
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That is: applying tests correctly; choosing appropriate tests for the data; identifying possible biases and confounders; correctly quantifying uncertainty; validating data; communicating results effectively; generally not p-hacking or otherwise committing statistical malpractice. ↩
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It is the same server I use to host this site. I manage the whole deployment myself from the command line. ↩