AI + Data Science + Product + Engineering
Senior Product Manager working at the intersection of agentic AI, clinical workflows, and human-centered product design in life sciences.
I'm a results-driven engineering leader with 10+ years working across big data, AI, and product management. I've been a software engineer, a data scientist, a DevOps practitioner, and a product manager — sometimes all in the same quarter.
That breadth isn't accidental. When AI makes decisions that affect real outcomes, the people using those products need to understand why, trust the process, and feel empowered rather than replaced. Solving that problem requires understanding the full stack: the models, the data pipelines, the user experience, and the business context.
"Building products where decisions are taken by AI requires the right information architecture and a deep understanding of how humans adopt new workflows. I think about this every day."
I lead agentic AI initiatives that transform clinical operations in the life sciences industry. I have strong ideas about applying the same principles across healthcare, finance, and education — and I'm actively building toward that future.
Too many AI products fail not because the technology is wrong, but because they don't meet users where they are. Clinicians, researchers, and operators need AI that fits naturally into their existing workflows — not the other way around.
I've spent my career learning to bridge the gap between what's technically possible and what people will actually trust enough to use. That means deep domain expertise, rigorous attention to how information is presented, and a product mindset that prioritizes outcomes over features.
AI decisions need context. I design products that surface the why behind every recommendation, giving users confidence to act on AI-driven insights.
Technology adoption happens when products respect existing processes. I build AI that augments human expertise rather than trying to replace it wholesale.
Great AI products prove their value through measurable impact: faster clinical timelines, more accurate assessments, reduced manual effort, better decisions.
A progression from hands-on engineering to leading AI product strategy at scale.
IFC / World Bank Group
GWU Marketing Dept.
JHU Center for Talented Youth
TIC Camp
GWU Psychology Dept.
GWU Athletics Dept.
Encircle.io
Unisys (US Homeland Security)
Pixellete
GripStreet
Generative AI and Large Language Models certification from NVIDIA.
Building AI solutions for 5+ products in life sciences R&D as certified product owner.
Recognized for outstanding impact on a flagship AI product line.
Fastest product launch in the organization's history.
Collaborative team achievement recognized by leadership.
Silver award for driving high-performance engineering culture.
Winner at Google DevFest DC hackathon.
Open source contributor to the LangChain framework.
Published in-depth technical blog series on AI and product development on Medium.
Coursework: Big Data & Analytics, Advanced Software Paradigms, Design & Analysis of Algorithms, Linear Algebra for ML, Probability for ML, NLP with IBM Watson
Highlights: International Student Ambassador, Global Tuition Fellowship, Research Assistant, CS Tutor, Teaching Assistant
Coursework: Databases, Android Development, Software Design, Computer Architecture, Computer Security
Highlights: Co-convener of Quiz Club, Led 5-person startup team, SESCON Hackathon Winner 2014
I write about building AI products, the intersection of technology and user adoption, and lessons from the trenches of product management in life sciences.
Visit the blog The AlmanackWhether it's about AI product strategy, agentic systems, or just an interesting conversation — I'm always happy to chat.