Dr. Daniel Wooten
AI/ML Software Engineer
Daniel Wooten
About Me
I have a passion for solving complex problems with straighforward data driven solutions.
With more than 5 years of experience developing, deploying, and analyzing AI/ML models, I know a thing or two about going from a customer need to a served solution. That road begins and ends with good teams and good teams are built on great communication. Having worked with many different people across different backgrounds and projects I look forward to finding out how we can work together on our most pressing challenges.
Aside from a lifetime of team-building and leadership, I have developed deep expertise in AI/ML model development and management. From whiteboard to user manual to government audits, I have seen projects through every stage of the development pipeline. My focus is data-adaptive algorithms utilizing data to inform business decisions; i.e. artificial intelligence and machine learning.
Recent Experience
1.5+ years as a Principal Data Scientist for Capital One
The move from a small research firm to a Fortune 500 firm was certainly a change.
From communicating across and up business verticals to shifting my delivery
mindset from exploration to production, I've learned how to maximize my value
add and make my own mark to Capital One. What I've found at Capital One is a place
where my passion for innovation is not only celebrated, but put to good use.
One of my best experiences at Capital One has been advancing the use of Transformer
(LLM building block) based models at Capital One within Anti-Money Laundering (AML). From my
start in AML I had a hypothesis that Transformer based models, with their ability to
find patterns in associative data, would be an ideal fit for the AML space. Over several
months I advocated this idea both to my peers and to leadership. While the idea had traction,
progress wasn't moving fast enough for me. To remedy this, after hours, I began building a
proof-of-concept Transformer based AML model. The success of this model, which I presented
to Data Science leadership, moved the needle and in the next few weeks I was overseeing an
intern project to explore additional avenues of Transformer usage.
From the heart of AI
A graduate degree from UC Berkeley
As the data science revolution began in the San Francisco Bay area so to did my graduate work as I started my Ph.D. at UC Berkeley in 2013. My thesis, already centered on the use of 1000 GB+ data sets, quickly became interwoven with the rapidly expanding data community at UC Berkeley. Having been an original member of the Berkeley Institute for Data Science I more heavily integrated data science and machine learning into my thesis, qualifying for and earning my designated emphasis in computational and data science engineering.
Previous Experience
AI/ML Engineer at Perceptronics Solutions
At Perceptronics Solutions I had the opportunity to architect and build two separate Bayesian inference systems: one for inferring a drone-operator's mental-state and another for assessing the likely ethical consequences of a battlefield decision. Each made use of Multiple-Hypothesis Tracking across diverse state-spaces. The most significant challenge in each project was translating subject-matter-expert's knowledge and intuitions into actionable insights and algorithms. My greatest technical challenge at Perceptronics Solutions was certainly the design and development of a real-time city-wide Multiple-Object Targeting and Tracking solution. This opportunity gave me the chance to take a deep dive into recursive Generalized Multi-Bernoulli filters - a state-of-the-art solution for unlearnable targeting and tracking environments.
What do I bring to your team?
Aside from a skilled software developer with machine learning expertise...
Business Sense
It's not about fancy algorithms, it's about value added to the consumer.
Communication
Is the glue that binds any team together which is why it's featured here.
Scientific Background
I've spent years honing the skills to know the unknown - let's shed some light on your unknowns.