The cambium is a layer in trees located just inside the inner bark. All new cells spring forth from here and become new wood that makes up the rings. All growth in a tree comes from the cambium.
Cambium Consulting is the growth layer for your new technology.
Daniel has spent over two decades in the software industry. He’s worked on a myriad of projects ranging from large scale distributed systems spanning hundreds of systems in EC2, to a digital school with an adjustable assessment engine, to large scale lab management software. He’s written lexers, parsers, and an internal DSL for testing media based hardware. Daniel has worked for large companies like NBC-Universal, Comcast, BellSouth, and VMWare, as well as startups like RoundBox Media, Sonian, and SnuggHome. He brings a wealth of relevant experience to Cambium, as well as a pragmatic approach to solving problems. Daniel loves teaching and currently serves as a mentor for the Turing School of Software Design.
Ian has enjoyed solving problems and building things using computers for as long as Daniel has. He likes building large scale fault-tolerant distributed processing architectures and data pipelines, writing code in Clojure, ClojureScript, and Python, and bringing order to chaos by practicing devops and agile development, optimizing business and technical processes, and comprehensive automation.
John started his career at Bell Labs where he was a developer for a database system, and two real-time switching systems. He was then a project manager specializing in large, complex projects and a technical manager for architecture and system requirements, after which he owned and managed a printing and marketing support firm. Recently, he has been developing applications in Clojure and ClojureScript.
Amber’s superpower as a data scientist is the interdisciplinary nature of her experience and thinking. Trained in a variety of quantitative methods, she’s leveraged digital analytics to increase user engagement, economic modelling to manage risk in a solar asset portfolio, and machine learning to predict consumer behavior. She loves to build, measure, and bring to light evidence to direct decisions big and small.