Experienced design leader creating simple solutions, for complex domains.
Product designer based in San Francisco designing enterprise tools and products for the past 10+ years, leading projects and managing design teams at GE, Google Cloud and Google Maps, Radar, and currently the Founding Design Lead at Motif.
tl;dr
I lead product design for complex domains by using my skills as a designer, grounded in the power of creative exploration from art, iterative feedback loops from the scientific method, and focusing the design intent on the user.
Design is a means to an end – to evoke an emotion, achieve a business goal or performance metric, retain talent and keep a brand relevant, and so on – without defining the end, the work will ultimately fall short.
You’re not making change unless you’re making. As a designer, I’m an idealist at heart, a realist in practice, with a strong bias for action.
on design
Inventing Sequence Analytics
Motif - Founding Design Lead
motifanalytics.com
Today’s analytics tools were built for “what” questions and often fail to answer more open-ended “why” and “how” questions, because answering exploration questions is structurally different from reporting ones.
We set out to build 3 key innovations to change how questions of data are expressed, queried, and ultimately visualized.
I lead design for the entire product and user experience, including our web and content marketing. Everything you see, is my fault.
Developer Onboarding
Radar - Director of Product Design
radar.com
Radar is the leading geofencing platform for developers and product builders looking to easily leverage location in their product experiences.
Location is hard, and getting up to speed on core location concepts and technology can be daunting.
I lead design to improve developer experience for free and enterprise customers, getting them acquainted with location and activated on the Radar platform.
Case study available upon request
ML Labeling Tools & Experiments
Google Maps - Design & Experiments Lead
Google Maps leverages machine learning (ML) to accelerate and automate the curation and maintenance of its vast network of map data. Training and maintaining those models requires the right tool, experience, and workforce to do so efficiently.
I lead two experiment teams for places and road data to increase efficiency of data labeling and output precision and recall, to unblock the scale and quality needed to automatically map the world.
Case study available upon request
