Machine Learning Engineer & Data Science Manager. I lead Generative AI for Capital One's contact centers.
At the start of 2018 I'd just finished a math and business degree at Baylor and had no idea where my career was headed. After some honest reflection, I committed to learning everything I could about machine learning and the tech industry — teaching myself, writing about it, and taking on freelance and research work while I earned a master's in Computer Science from UT Dallas.
Six years later, I'm a Data Science Manager at Capital One, leading Generative AI for our contact centers. My teams build real-time, LLM-powered tools that help thousands of servicing agents mid-conversation — agentic summarization, retrieval-augmented generation over live transcripts, and streaming sentiment and complaint detection. Along the way I've also built the auto-loan underwriting models that decision loans at large scale. I care most about taking hard, ambiguous problems from prototype to production, and about the measurable difference that makes for the people on the other end.
Expand a role to see what I built there.
Research work on emotion classification over population-scale social data — the start of the NLP thread that runs through everything since.
Taught data science on-site at Intuit — the habit of explaining hard technical work to people who don't do it for a living has been useful ever since.
Anomaly detection on billing systems — finding the handful of records that mattered inside a very large, very noisy pipeline.
Capital One's first real-time AI alert system — streaming DistilBERT and LLM sentiment over live calls at scale, alerting managers to de-escalate in real time.
Architected parallel real-time inference pipelines sustaining high throughput at low latency on Kafka, AWS Lambda, DynamoDB, S3, and Snowflake, monitoring live calls at production scale.
Just as important, I built the observability and governance around these systems — dashboards and alerting in New Relic, PagerDuty, and Splunk — so a non-deterministic system can be trusted in production.
I lead Generative AI for Capital One's contact centers — real-time, LLM-powered and agentic tools that augment thousands of servicing agents live, mid-conversation. Recent work includes an agentic call-summarization pipeline that trims after-call work — material projected operational savings at full rollout — retrieval-augmented generation over live transcripts, and an LLM complaint-detection system that sharply lifts complaint capture at high precision (piloting in 2026).
I'm the de facto lead of a ~10-person cross-functional team — two product managers, a software engineer, a data engineer, and five annotators — through influence rather than formal authority, plus two applied-research pods and a three-engineer pipelining team I negotiated for when the roadmap outran my hands. I set technical objectives with VP- and EVP-level stakeholders and lead annual roadmapping that aligns our investment with business priorities.
