Project Managing research activities is hard; the open ended nature of research makes it too easy to meander aimlessly through the available time and budget. Good project management won't help you find the solution to the problem but it may stop you wasting time getting to a conclusion. In the competitive world of commercial data science, project management could be the difference between market success and obscurity. Photo by Eden Constantino on Unsplash Background Some of the history has been simplified to avoid allowing the original project and corporate complexity to detract from the key points. In 2017 we started our first project with data as a primary component, and data science as a necessary skill. We were not creating a new type of model, but we were aiming to deliver a product based on a function for which no pre-trained model existed at the time. We started hiring a "mixed bag" of PhD. data scientists and dived in. 2 main problems started cropping up: It took
Lightweight Conjecture Records for Research Teamwork Intended for Data Science AI/ML Research Teams, but generally applicable. Slug conjecture-records-improve-research-teamwork Context Data Science is now a first class citizen of the technical world, but that is only a recent development and it still lags behind hardware and software in terms of ecosystem maturity. One area that is still behind the curve is the area of teamwork and working on large scale objectives. From Fred Brooks to Michael Nygard the software and system architecture challenges have always been the same - how best to communicate the solution in your head. So following in the footsteps of LADR files, and in the style of the original post ... Conjecture We posit that keeping a collection of "domain significant" conjectures will improve research teamwork; these conjectures put forward experimental thinking that affect dimensionality, data characteristics, pre-processing options, calibrations, qualitative ana