Pros
Nuna has a socially important mission – to make healthcare more affordable and accessible, on a large scale. Nuna has indeed demonstrated some successes in this area, for instance, they introduced modern cloud computing methodologies to the large, stodgy institutions that control healthcare, including the Medicaid administration. Jini Kim, the CEO, is very charismatic and has managed to introduce some SV tech culture into the normally dull and buttoned-down domain of healthcare insurance analytics. Nuna has good financial backing and as a result has been able to make large-scale sales to government and big insurers, that is, to large conservative institutions that normally wouldn't dream of dealing with a young startup. Nuna put a lot of emphasis on having a compassionate and progressive culture, on inclusion and diversity and personal growth. This is mostly a plus but see below.
Cons
While Nuna is a mission-driven company, the actual mission is disguised under a cloud of self-righteous rhetoric like “every row of data is a life” (an oft-repeated company slogan which typifies the empty virtue signalling). Despite the loud devotion to compassion and helping sick people, Nuna is not in the health-care delivery business or anything close to it, but rather the cost containment business. Their customers are organizations that spend a lot of money on health care; the service Nuna provides is to help reduce that spend or make it more effective. There՚s nothing wrong with that – helping keep health care spending under control is a perfectly useful thing to do, but it՚s not very inspiring. It՚s far removed from the actual practice of medical care, and thus not really the kind of thing that deserves any special recognition for compassion, any more than an insurer like Blue Cross does. It՚s a business. And Nuna is not alone in this business, there are quite a few bigger and more established companies in this space (such as Optum and Truven, now part of IBM). Nuna՚s advantages against these competitors are minimal, mostly rooted in having more Silicon Valley cachet. Putting health care data in the cloud was innovative a few years ago, now there are a great many people doing it. Nuna՚s cachet enables it to attract some talented engineers, but it doesn՚t really know what to do with them.. There՚s very little interesting engineering innovation happening at Nuna; the data science is competent but nothing special as far as I can tell. The big technical innovation that drove the company originally was heavy use of AWS, but that is no longer much of a distinguisher. Unlike some of these older companies, Nuna is hobbled by restrictive data agreements that limit the uses they can make of all the data coming through their system – that is a serious business risk, especially given machine learning՚s need for massive datasets. If Nuna can՚t combine their customers data, scaling the business will not scale their ML capabilities accordingly. The data that Nuna does handle is limited to insurance billing records, and this too is pretty far removed from the actual practice of healthcare or the advancement of medical science. This may have changed since I was there, certainly there was talk of making use of EHR-level data, but again, Nuna has very little connection to the practice of medicine and probably wouldn't know what to do with data like that. Culturally Nuna has a serious problem in hyper-political-correctness. Diversity is one thing (and something Nuna does very well); but constant pledges of fealty to approved values are something else again. Many companies do this now to some extent but Nuna takes it to extremes, to the extent that it can create an oppressive atmosphere and alienate people in the name of inclusion. In part because of this, Nuna has had trouble retaining senior engineers, and there is very little in the way of coherent technical leadership. There are serious gaps in technical strategy -- perhaps because management is focused on other things. In short, Nuna is a good place if you care most about diversity, and want to spend a lot of mental energy on things like making sure nobody uses words like "guys" for a mixed-gender group. It is not a very good place if you value creativity, innovation, or learning. And if you really care about improving health care you should probably work on that directly, not on better analytics for payers.
