Michael Swindle
Cleared Data Analyst & Information Operations Professional
Data analyst, information operations professional, and Army officer with joint strategic and operational planning experience. Background in capability development and experience in machine learning and data engineering.
I specialize in translating complex problems into actionable insights for decision-makers.
About Me
I’m a data analyst and field-grade Army information operations officer with joint, strategic, and operational planning experience. My background also includes law enforcement and military logistics. I’ve built machine learning models and data pipelines using Python, R, and Palantir Foundry, and I regularly work with statistical modeling, natural language processing, and dashboard development to turn incomplete or disorganized data into something useful.
Beyond what is documented in my resume, what I really bring to the table is an ability to work through ill-defined problems, with imperfect tools, and under sub-optimal conditions. I approach challenges from the perspective of finding how to “get to yes”, and I have come to enjoy the process. I like figuring out what’s needed, learning what I have to, and just getting things done.
If you are looking for someone in one of the fields where my experience stands out, I am fully qualified and ready to make a difference in your organization. However, if you're not entirely sure what you need and looking at problems that don’t easily fit into one domain, I have some experience with that too.
Featured Projects
I started this project to sharpen my technical skills and to showcase the work that doesn't fit well on a resume. I’ve included a selection of my projects below, which I will be adding to in the near future. If you want to hear more details about my work and get some insights into how I think, you can check out my blog which is currently in development. More content coming soon.
Crime Data Analysis:
Copper Theft in the DFW I-35 Corridor
An analysis of copper theft patterns during the 2000s metal price surge, focused on industrial hotspots along I-35 in the Dallas–Fort Worth area. Combines historical pricing data, geospatial mapping, and LE strategy recommendations.
NLP with Disaster Tweets:
Kaggle Classification Competition
A series of NLP experiments aimed at classifying tweets as real or non-disaster related. Compares TF-IDF and Word2Vec pipelines using XGBoost, with performance measured on Kaggle’s public leaderboard.