Scott Williams - Personal Website

About Me

Hi I'm Scott, a graduate of The Colorado School of Mines with a Bachelor's in Computer Science and focus in Applied Math. After my May graduation, I'm looking forward to be returning in June as a Data Engineer at iCapital in NYC on the Data & Analytics team where I interned last summer (2024).

During my education, I have learned about computer science theory and its connection to mathematical concepts. This knowledge has been incredibly useful in furthering my experience and understanding of the ML/AI field as a whole. After my internship at iCapital I gained invaluable experience contributing on a software team and architecting scalable solutions in the cloud.

Since I tend to learn best through consistent, project-based activities, I decided to deepen my AWS understanding this fall (September - December 2024) by constructing a data pipeline to collect highly granular order book data and publicly available weather measurements, with the goal of automating arbitrage trades based on my speed advantages on the daily weather prediction markets of Kalshi. This data collection system functioned as expected, and ran uninterrupted for a month, but liquidity issues on the prediction market did not present ample scale to make the system profitable, when adjusting for cloud costs. Through this project, I gained practical experience architecting fast and efficient cloud solutions, and improved my cloud development workflow by adopting infrastructure as code to create resources on AWS.

In summary, all of my seemingly unrelated projects have taught me that I am interested in many fields, especially those related to AI/ML, cloud computing, and the technology space as a whole. In addition to my passion for building software solutions, I'm a lifelong athlete. I have been playing hockey since I was 6 years old and was captain of my rowing team at The Taft School. I also enjoy playing poker, hiking, running, and reading new AI research papers. Thanks for visiting my website, and feel free to reach out via any of my socials linked above.

Work Experience

iCapital, Data Engineering Analyst (June 2025 - Present):
Building document parsing pipelines to assist business stakeholders with repetitive document searching / Information Retrieval processes. Migrating existing data pipeline orchestration tooling to a new provider. Refactoring old code and infrastructure to be more efficient and scalable.
iCapital, Data Engineering Intern (Summer 2024):
Researched Snowflake usage attribution and built DBT models supporting Tableau dashboards.
Colorado School of Mines Career Center, Student Assistant (2022-2024):
Coordinated Career Day and resolved technical issues for students and faculty.
Coolipy, Open Source Contributor (February 2025 - Present):
Collaborated with maintainers to identify and resolve bugs, contributing merged fixes to the Python client library for Coolify.

Awards

Meta Llama 4 NYC Hackathon 2nd Place ($5k Prize) (June 2025):
Competed in a 24 hour contest against hundreds of talented developers to build AthletIQ, a personalized AI coach which gives athletes feedback based on video footage from any sport. Achieved 2nd place overall in the contest.
Demo Video, Hackathon Presentation, LinkedIn Post, GitHub Repo.

Projects

SaaS Factory: Developed a CLI tool that automates VPS provisioning and configuration for rapid SaaS deployment. The tool spins up Linode instances (with plans to extend to additional providers like Hostinger and AWS EC2), automatically installs Coolify for VPS management, and configures open source products including N8N, Supabase, and Prefect. Additionally supports deployment of fully hosted Next.js starter applications with GitHub webhook integration for seamless CI/CD workflows, enabling developers to launch production-ready SaaS products in minutes with less than 5 commands and limited UI interaction. Currently documenting the tool to make it more user-friendly and accessible to developers of all experience levels.
CaveatBot: Built a VS code extension in under 36 hours for a hackathon. The extension records all code changes, commands and their output, screenshots, and notes and adds them to a knowledgebase, allowing fast and efficient querying to recall configurations made to a project using Groq for fast inference and Pinecone's vector DB.
Model Fine-Tuning & Synthetic Data Generation Micro-Project : Created a pipeline to filter and label reddit content for finetuning jobs using small open source models. This was ultimately used to fine tune the 1 billion parameter gemma 3 model to run locally for easy json extraction. Link to model: Hugging Face Model and link to dataset: Hugging Face Dataset.
News Video Generator: This project automates the creation of short-form videos for TikTok and Instagram based on a topic prompt. It leverages web scraping to source recent news articles, utilizes semantic search and GPT-4-powered script generation, incorporates a custom text-to-speech API for narration, automates image sourcing, and integrates dynamic "white noise" video. Using FFMPEG for fast and automated video processing, the gathered assets are seamlessly organized and rendered into engaging, high-retention content optimized for social media platforms. See sample posts on Instagram: World News Daily & Tech News Daily.
Personal Portfolio Builder: Created a chatbot to quickly generate and edit professional-quality portfolio websites.
Clue Game Project: Recreated the game of Clue using Java with Test Driven Development and collaborative coding.

Skills

Programming Languages:

C++, Java, Python, OCaml, JavaScript, Jinja2, R, TypeScript

Web Development Frameworks and Tools:

Angular, Next.js, React, Auth.js, Lucia Auth, Supabase, PocketBase, Cloudflare

Data Management:

PostgreSQL, MySQL, Snowflake, DBT, Vector Databases, Airflow, MongoDB

Cloud and Virtualization Technologies:

AWS (Lambda, EventBridge, MWAA, EC2, ECR, RDS), Google Cloud, Docker, Linode (VPS), Coolify (VPS management software)

Networking and Proxy Management:

DNS, Traefik

AI Engineering and Large Language Models (LLMs):

LangChain, Vector Databases, Model Fine-Tuning, Model Quantization, Synthetic Data Generation

Machine Learning and Statistical Modeling:

TensorFlow, Transformers, Scikit-Learn (SKLearn), SciPy, OpenCV, Time Series Analysis, Linear/Polynomial Forecasting, Stochastic Modeling (Markov Chains, Poisson Processes, Brownian Motion)

Video Creation and Editing:

FFMPEG, GarageBand, Adobe Premiere Pro, Clipchamp

Project Management:

Agile, Test-Driven Development (TDD), Design Documentation and Review, Sprint Planning

Terminal and Tools:

Bash, PowerShell, Git, AWS CDK

Education